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Energy efficient TDMA-based MAC protocol associated with GAF for wireless sensor networks
THE JOURNAL OF CHINA UNIVERSITIES OF POSTS AND TELECOMMUNICATIONS Volume 14, Issue 1, March 2007
XlAO Xiao, ZHENG Bao-yu, YAN Zhen-ya, CHEN Chao
Energy efficient TDMA-based MAC protocol associated with GAF for wireiess Sensor networks CLC number TN9 15
Document A
Abstract The design of media access control (MAC) pt-1 for wireless sensor networks CNSNs) with the idea of cross layer attracts more and more attention. People can improve the MAC protocol by obtaining certain information regarding the network layer and physical layer. This article synthesizes and optimizes certain cross-layer protocols which have existed. On the basis of the routing, topology information in the network layer, and transmission power information in the physical layer, the time slot assignment algorithm has been improved in the MAC layer. By using geographical adaptive fidelity algorithm (GAF) to divide the grids, controlling of transmission power and scheduling the worklsleep duty cycle for sensor nodes, a new MAC protocol has been proposed to decrease energy consumption and enlarge the lifetime of WSNs. Simulation results show that the MAC protocol functions well. Keywords power controlled, time division multiple access (TDMA), WSNs, MAC, GAF
1 lntroductlon WSNs developed at a rapid pace because of the advance in embedded system’s integration arts and crafts in the recent years. WSNs mean a network, which includes hundreds or thousands of sensor nodes randomly deployed in a wide area. The network is responsible to organize and send all kinds of information that it senses and receives. Due to this function, the WSNs realize the communication between human beings and natural world. Lack of energy is the major problem for the functioning of WSNs. So, the solutions for energy efficiency have been researched in all layers. Recent researches focus on the design of cross-layer protocol. By sharing the information in every layer, the WSNs save a lot of energy and hence enlarge the lifetime. References [I, 21 describes the GAF protocol which divides the Recewed date: 2006-08-23 XJAO Xiao (Z-Z), ZHENG Bao-yu, YAN Zhen-ya, CHEN Chao Institute of Signal and Information Pressing, Nanjing University of Posts and Telecommunications, Nanjing 210003, China E-mail: unwoman8sohn.com
Article ID 1005-8885(2007)01-o006-06
inspective area into certain virtual grids and places the nodes into the respective grid on the basis of thek geographical information (e.g. coordinate). In every grid, the nodes will select a cluster head. Only the head has the right to communicate with other heads when the normal nodes which do not become the head fall into sleep in order to save energy. The detail of the protocol will be discussed later. Reference [3] describes a TDMA method for designing the time slot on the basis of vertex coloring algorithm. Reference [4’j describes an energy eficient protocol on the basis of controlled power with multiple transmission levels. Moreover, Refs. [5-91 also contributes certain useful ideas for MAC protocols. Reference [ 101 is beneficial to this study for cluster management. Although these protocols decrease the energy consumption in one aspect, the energy will be wasted in other aspects. Hence, it was considered to integrate the advantage of grids division in GAF and time slots division in TDMA, and finally a more efficient protocol was obtained for saving the energy assumption: A power-controlled MAC protocol associated with GAF for WSNs. It can also be referred to as GPCMAC. The remainder of this article is organized as follows: Section 2 gives the details on the related studies. Section 3 presents the study for integrating certain useful protocols and the improvement in the protocol. Simulation results and performance comparisons are shown in Sect. 4. The article is concluded in Sect. 5.
2 Relatedrkrdb Many WSN protocols have been developed in recent years. One of the earlier studies, GAF, was to select a cluster head in every grid on the basis of the node’s coordinate. In the grid, only the cluster head was awake when the other nodes fell into sleep. There are two phases in the GAF algorithm. The grid is divided in the first phase. It was assumed that the network plane is divided into virtual R X R grid (see.Fig. I). Each cell has a size r>&R, which is computed with R2 + ( 2 R ) ’ d r 2 , where r is the nominal radio range of the sensor nodes. This cell size guarantees connectivity of the whole sensor field.
No. 1
XIAO Xiao, et al.: Energy efficientTDMA-based MAC protocol associated with GAF for wireless sensor networks
7
difficult to make enough nodes work in a single time slot. The advantage of vertex-coloring algorithm is not obvious.
8 A p o w e r c o n t r o ~MAC ptalocol assodatd wlth QAF for WSNs Fig. 1 Radio range in a grid
The second phase of GAF algorithm denotes the method to select the cluster head. The nodes switch the status between sleeping and working which include the status of discovery and being active. When the node wakes up, it exchanges information with the other nodes in the same grid. Then the node will know whether it has become the cluster head. Every node has three statuses, respectively, discovery, active, and sleep. All the nodes will be in the discovery status when the network is initialized. Every node has the sleep timer, discovery timer, and active timer. Depending on these timers, the nodes can have a contention for the cluster head reasonably, and switch the status in sleeping, discovery, and active status, which is selected by the cluster head. PCSMAC [4] improves the SMAC protocol on the basis of the level of multiple transmission power. It reduces the probability of data collision and overfull control information. This protocol improves the energy efficiency on the basis of different controlled power of RTS, CTS, ACK, and DATA. In general, the power of RTS, CTS, and ACK is stronger than the power of DATA because the control information should be strong enough in order to be accepted by every neighbor nodes that will fall into sleep avoiding interruption of working nodes communication. CoLaNet [3J protocol describes a vertex-coloring algorithm, which is used to divide the TDMA time slot. The nodes can communicatein an undisturbed environment because the nodes which may cause disturbance are put into a different time slot on the basis of vertex-coloring algorithm. The sensor nodes closer to each other have similar sensed data. So, if these nodes transmit the data to the father node, it will be a waste of energy and compel the father node to consume more energy when it aggregates reduplicate data. Furthermore, the SINK node that broadcasts the time slot assignment rule will increase the time slots for more transmission channels. It enhances the delay of the network. If the GAF is utilized to divide the grids, it will avoid the nodes from transmitting the reduplicate data. However, the problem also exists because the node is randomly disposed, and so certain parts of the area may contain too many nodes. The density of the nodes in this area is so huge that even the GAF is used, and the interference is still large because the size of the grid is too small. Even the vertex algorithm is used, and it is
For standing out the advantage of vertex-coloring algorithm, the power is controlled on the basis of the principle referred to in Refs. [4, 111. The time slot assignment algorithm and channel interference algorithm referred to in Ref. [3] was also improved. On the basis of the different target nodes, the transmit power dynamic was changed, and so the interfering range of the source node is diminished. It reduces the interrupting probability of “source-4estination pair”, so less time slots will be divided, and in this manner, more nodes will work in one time slot. The efficiency of every time slot is enhanced due to the improvement. The probability of data overflowing as a result of the full buffer is reduced and the delay of the network is also reduced. Moreover, owing to the reduction in transmission power, the whole sensor radio module consumes less energy. More energy will be saved for the single node and the whole network. Figure. 2 shows the protocol stacks that are divided into four phases: GAF topology establishment phase, time slot request, and broadcast phase, data sending phase, and sleeping phase. GAF Tuneslot , Data topology request and’ sending Sleeping phase establishment broadcast ’ phase phase Phase II
1
I
I
/First time slot in it
II
t/ Working phase
I
I
I
Fig. 2 GKMAC protocol stack
3.1 GAF topology establishment phase After achieving initialization, the nodes will identify their location by communicatingwith each other and the grid will be divided in virtue of the GAF rule. The SINK node which is the head of all nodes will broadcast the grid distribution result to every node on the basis of the location information which the nodes have informed to SINK node. After deciding the gridb, the nodes compete for the cluster head in their respective griil. The nodes which become head sense and transmit the data aqd the failure nodes fall asleep when their sense modules keep working. When the sleep timer reaches timeout, the sleepy node transfer competes for the cluster head again. But the competition for head is a random action. The process may interrupt the time slot for data transmission which has been assigned by the SINK node, so the protocol assigns a unique time slot to compete for the cluster head. The competition time slot is assigned to every node as the
The Journal of CHUPT
8
first time slot in the protocol stack which has been described in Fig. 2. Zn this manner, the current cluster head will stop the transmission of data to other heads in the first time slot, and it will participate in the competition for the head in its own grid. Now, the problem is how to make the sleepy node master the moment fmt time slot start at. The current head node is easy to know when the first time slot starts because of the SINK node's broadcasting, but the sleepy nodes are difficult to identify when the fmt time slot starts because they cannot receive the broadcast message from the SINK node. For this reason, every sleepy node is compelled to hear a little time when they wake up. Until the SINK node broadcasts the new time slot assignment, all nodes will compete for the head in the new first time slot. Original GAF algorithm requires that the nodes participate in the head competition immediately when they wake up. But, it is easy to cayse data collision. Hence, the protocol delays a little time for the nodes which is not the head to ensure no interference for data delivery ratio. In the simulation, it was found that it did not affect the delay in performance. So,it is reasonable for selecting the cluster head. 3.2 Time slot request and broadcast phase
The cluster head in every grid will inform their sending request to the SINK node in this phase, and then the SINK node will decide the time slot division as the following algorithms and broadcast the decision to every head on the basis of their node ID and grid ID. 3.2.1 Decide the least transmission power
In Refs. [4, 111, the author provides certain equations to calculate the least transmission power. There are four equations as folIows:
p =-44
" P ,
(3)
Pm=-C 44 (4) P, where P is the transmission power, A is the carrier wavelength, n is the path loss coefficient, Gt is the transmitter antenna gain, and G, is the receiver antenna gain. The value of n is usually between 2 and 6 depending on the physical environment. In order to provide the minimum necessary received signal strength index (RSSI) for the reception of a frame; the minimum transmission power level P, at the source node is calculated as Eq.(2). Rt is the w i v e d power when the source node transmits with P,. By combining Eqs. (1) and (2), Eq. (3) is obtained, in
2007
order to cope with the inaccurate estimation of the channel fading characteristic, the calculated P, can be multiplied by a preset coefficient C as in Eq. (4). If a receiver node knows the transmission power level used by the sender node Pt, with a known R,, and measuring the power level for the received frame Pr,it is possible for the receiver node to calculate the minimum required transmission power level P, to send a frame back to the source node using EQ.(4). 3.2.2 Time slot assignment algorithm
The slot assignment algorithm referred to Ref. I31 is introduced, and in a word, there are three conditions (on the assumption that '' a -+ b " represents the link between node a and node b, the rest communication links may be deduced by analogy): 1) a + c and b + c cannot exist in the same time slot 2) a + b and a -+ c cannot exist in the same time slot, too. 3) When a + b interferesc -+ d , the two links cannot exist in the same time slot, and vice versa. The links which cannot exist in the same time slot are looked upon as the points which cannot color up the same color. The vertex-coloring algorithm can be used to color up every communication link. The link which colors up the same color can be taken into the same time slot. That means the number of colors determine the number of time slots. 3.2.3
Channel interference algorithm
The third condition in the time slot assignment algorithm refers to the channel interference algorithm, and the protocol predigests it. Because of the control to the source node's transmission power, every source node reduces its range of interference, which basically equals the distance between the source and the destination. So, the algorithm that was used (was on the assumption that the distance between node a and node b is described as ab, the rest distance may be deduced by analogy): if one of the four conditions which are a b 3 a d , a b 3 ac, cd3cb, c d 3 c a come into existence, the link a + b and link c + d interfere with each other, and hence cannot exist in the same time slot. 3.2.4 The fungible slgorithm for the accurate vertexcoloring algorithm A fungible algorithm needs to be selected for the accurate
vertex-coloring algorithm because it is too complex and every node's computational capacity is restricted in the simulation environment or in the actual environment. So, it was decided to use the Powell algorithm referred to in Ref. [12] to replace the accurate vertex-coloring algorithm. The concrete description is described as follows: 1) Every node in graph G is arrayed on the basis of the descending order of the degree which means the numbers
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XIAO Xiao, et al.: Energy efficient TDMA-based MAC protocol associated with GAF for wireless sensor networks
which are linked to the node itself: 2) Then one node is colored up with another color and another node is colored up with the same color which is not the neighbor to the former that has been colored up: 3) The second color is used to color up the node which has not been colored up by repeating 2). Then the third color is used to carry through the similar action. The process is complete only when all the nodes have been colored up. 3.3 Data sendlng phase Every node will transmit the data without collision, competition and overhear in the time slot which is divided on the basis of the above-mentioned algorithm. The energy consumption is smaller compared to CoLaNet protocols when the nodes transmit the same amount of data because of smaller transmission power. The energy consumption is divided into two parts. One is the consumption in the radio module; the other is used for the working of the internal circuit. In the simulation, the internal consumption is set to a constant value, and the consumption in the radio module is set to a variable which is altered with the transmission power. 3.4 Sleeplng phase
The sleeping phase follows the working phase. The node moves to the working phase (discovery status) automatically when the sleep timer reaches timeout. Considering that the node may become a failure and so new nodes may be deployed in the networks, the topology of the network may be altered; moreover, the amount of the data will also be variable. So, the transmission power and the time slot should be recomputed after a fixed time. Reference [13] proposes to utilize a scheme to broadcast for setting up a phase-switching schedule against establishing a constant time slot assignment in the network and design a reasonable time slot allocation mechanism on the basis of the traftic strength and unsuccessful transmission rate. This adaptation issue is an ongoing effort and is beyond the scope of this study.
9
“CoLaNet” and the “Normal TDMA” associated with GAF are also simulated. NS2 introduced in Refs. [14-151 was used to achieve the simulation. The network includes 50 nodes in 500 mX500 m square area. Figure. 3 shows total energy consumption of 6 instances. GPCMAC shows that the total energy efficiency is better than other protocols and the lifetime is also longer. Energy analysis
/
Timds
Fig. 3 Energy assumption
Nine groups of simulations were processed on the basis of the different numbers of nodes and different sizes of square area for the performance of end-to-end delay which is defined as:
where Ed ,T, ,T, , and Ns, respectively, denote end-to-end delay, time for receiving packets, time for sending packets, and the number of sending packets. The fist group has 5 nodes in 50 mX50 m square area, the second group has 10 nodes in 100 mX 100 m square area, the rest may be deduced by analogy until the ninth group has 45 nodes in 450 m x 450 m square area. Figure 4 shows the Normal TDMA that shows the worst delay performance. CoLaNet’s delay performance is similar to the PCMAC. The GPCMAC used for this study has the best delay performance.
4 Slmulatlonrerults The protocol that is described is entitled “A power controlled MAC protocol associated with GAF‘ and it will be termed “GPCMAC” for short in the simulation. The “power controlled MAC protocol without GAF” is short for “PCMAC” to compare GPCMAC. Reference [3] refers to the CoLaNet that is expressed to “CoLaNet” in the simulation. Moreover, an original TDMA protocol is still used which denotes the number of nodes, number of time slots, and is expressed as ‘‘Normal TDMA” in the simulation. For an all-round comparison, The
*GPCMAC
Node numbers
Fig. 4 Delay performance
In Fig. 5, the performance of three different MAC protocols
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(GPCMAC, PCMAC, and C o m e t ) is compared in terms of the average delivery ratio of the data packets. Delivery ratio symbolizes the reliability of the network. It is defined as:
where, 0, $, and T, , respectively, denote delivery ratio, number of received packets, and number of transmitted packets. 1.Ooo
R
GetRatio analysis
0.999
.-0
0.999
E2. 0.998 0
'I
.z 0.998 0
*
$u 0.997
4
0.997
4-PcuAc -coLaNel -r GPCMAC
"I
0.9%05
10
15
25 30 Node numbers
20
\ 35
40
45
International Conference on Mobile Computing and Networking (MobiCOM 2001), Jul 16-21,2001, Rome, Italy. 2001: 70-84 2. Le Xuan Hung, Seo Dae Hong, Lee Sungyoung, et al. Minimum-energy data dissemination in coordination based sensor networks. Proceedings of 11th IEEE International Conference on Embedded and Real-time Computing Systems and Applications (RTCSAM), Aug 17-19, 2005, Hong Kong, China. Piscataway, NJ, USA: IEEE Computer Society, 2005: 381-386 3. Chou Cheng-fu, Chuang Kwang-ting. CoLaNet: cross-layer design of energy effiicient wireless sensor networks. Proceedings of the 2005 Systems Communications (ICW'OS), Aug 14-17, 2005, Montreal, Canada. Piscataway, NJ, USA. IEEEComputer Society, 2005: 304-369 Nar P C, Cayirci E. PCSMAC: a power controlled sensor-MAC protocol for wireless sensor networks. Proceedings of 2nd European Workshop on Wireless Sensor Networks, Jan 3 1-Feb 2, 2005, Istanbul, Turkey. Piscataway, NJ, USA EFB Computer Society, 2005: 81-92 Bao L, Garcia-Luna-Aceves J J. A new approach to channel scheduling for Ad-hoc networks. F'roedm . gs of 7th Annual International Conference on Mobile Computing and access
Fig. 5 Delivery ratio performance
The performance of GPCMAC decreases in some sort than other two protocols, but the difference is not obvious and can be ignored.
In this study, GPCMAC has been introduced, a power controlled MAC protocol associated with GAF for wireless sensor networks. This scheme is on the basis of GAF protoco1,vertexcoloring algorithm, and the minimal transmission power for saving energy and prolonging network lifetime. Vertex-coloring algorithm and minimal transmission power were employed to decide the least time slots in the network. The simulation shows that GPCMAC is successful in meeting the design goals of energy efficiency, good performance of delivery ratio, and end-to-end delay. The simulation also shows that the protocol increases the network lifetime successfully than other approaches, especially with high node density. Acknowledgements This work is supported by the National Natural Science Foundation of China (60372107) and Chongqing Key Laboratay Open Project Foundation.
References 1.
Xu Y, Heidemam J, Estrin D. Geography informed energy conservation for Ad-hoc routing. Proceedings of 7th Annual
2007
Networking (MobiCOM 2001), Jul 16-21, 2001: Rome, Italy. 2001: 210-221 6.
7.
8.
9.
Rajendran V, Obraczka K, Garia-Luna-Aceves J J. Energy efficient, collision-fke medium access control for wireless sensor networks. Proceedings of 1st International Conference on Embedded Networked Sensor System (SenSys'O3), Nov 5-7, 2003, Los Angeles, CA, USA. New York, NY, USA: ACM press, 2003: 181-192 Lu G, Krishnamachari B, Raghavendra C. An adaptive energy efficient and low-latency MAC for data gathering in wireless sensor networks. proceedings of International Paralled and Distributed Processing Symp (JPDPS'M), Vol 18, Apr 26-30, 2004, Santa Fe, NM, USA. Los Alamitos, CA, USA IEEE Computer Society, 2004: 3091-3098 Cui Shu-guang, Madan R, Goldsmith A, et al. Joint routing. MAC, and link layer optimization in sensor networks with energy constraints. Proceedings of International on Communications: Vol 2, May 16-20,2005, Seoul, South Korea. Piscataway, NJ USA: IEEE,2005: 725-729 Sun Li-min, Li Jian-zhong, Chen Yu, et al. Wireless sensor networks. Beijing, China: Tsinghua University Press, 2005 (in Chinese)
10.
Ho Shen-ben, Su Xiao. CuMPE cluster management and power efficient protocol for wireless sensor networks. Proceedings of 3rd International Conference on Information Technology Research and Education, Jun 27-30, 2005, Taipei, China. Piscataway, NJ, USA IEEEComputer Society, 2005: 60-67 11. Liu Guo-pei Madun-Jie. Radio and antenna. Changsha, China: National Defence & Science and Technology University Press,
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XU0 Xiao, et al.: Energy efficient TDMA-based MAC protocol associated with GAF for wireless sensor networks
2004 (in Chinese) 12. Xiao Wei-shu. Graph theory and its algorithm. Beijing, China: Aviation Industry Press, 1993 (in Chinese) 13. Ren Qing-chun, Liang Qi-lian. An energy eficient MAC protocol for wireless sensor Networks. Proceedings of Global TelecommunicationsConference: Vol 1, Nov 28-Dec 2, 2005, St Louis, MO, USA. Piscataway, NJ, USA: IEEE,2005: 5 14. Xu Lei-ming, et al. NS and networking simulation. Beijing, China: Posts and Telecom Press. 2003 (in Chinese) 15. Wang Hai-tao,Zheng Shao-ren. Routing protocols for Ad-hoc network & their performance comparisons. The Journal of Chongqing University of Posts and TelecommunicationsNatural Science, 2002, 14(4): 73-77 (in Chinese) Biogcaphies:XIAO Xiao, from Jiangsu Province, master Candidate, Nanjing University of Posts
and Telecommunications, interested in the research on signal processing, wireless sensor networks, mobile communication.
11
ZHENG Bao-yu, from Fujian Province,professor,
doctoral supemisor, Department of Information, Nanjing University of Posts and Telmmmunications, interested in the research on intelligence signal pmcessing, communication signal processing, and q u a n u tm signal pmesing, etc.
YAN Zhen-ya from Fujian Province, Ph. D. Candidate, Nanjing University of Posts and TelecommUnications, intemted in wireless sensor network, particle filter, cooperative diversity, etc.
CHEN Chao, from Jiangsu Province, master Candidate, Nanjing Univexsity of Posts and Telecommunications, interested in the research on signal processing, mobile Cwrmmunicaeion.
XlAO Xiao, ZHENG Bao-yu, YAN Zhen-ya, CHEN Chao
Energy efficient TDMA-based MAC protocol associated with GAF for wireiess Sensor networks CLC number TN9 15
Document A
Abstract The design of media access control (MAC) pt-1 for wireless sensor networks CNSNs) with the idea of cross layer attracts more and more attention. People can improve the MAC protocol by obtaining certain information regarding the network layer and physical layer. This article synthesizes and optimizes certain cross-layer protocols which have existed. On the basis of the routing, topology information in the network layer, and transmission power information in the physical layer, the time slot assignment algorithm has been improved in the MAC layer. By using geographical adaptive fidelity algorithm (GAF) to divide the grids, controlling of transmission power and scheduling the worklsleep duty cycle for sensor nodes, a new MAC protocol has been proposed to decrease energy consumption and enlarge the lifetime of WSNs. Simulation results show that the MAC protocol functions well. Keywords power controlled, time division multiple access (TDMA), WSNs, MAC, GAF
1 lntroductlon WSNs developed at a rapid pace because of the advance in embedded system’s integration arts and crafts in the recent years. WSNs mean a network, which includes hundreds or thousands of sensor nodes randomly deployed in a wide area. The network is responsible to organize and send all kinds of information that it senses and receives. Due to this function, the WSNs realize the communication between human beings and natural world. Lack of energy is the major problem for the functioning of WSNs. So, the solutions for energy efficiency have been researched in all layers. Recent researches focus on the design of cross-layer protocol. By sharing the information in every layer, the WSNs save a lot of energy and hence enlarge the lifetime. References [I, 21 describes the GAF protocol which divides the Recewed date: 2006-08-23 XJAO Xiao (Z-Z), ZHENG Bao-yu, YAN Zhen-ya, CHEN Chao Institute of Signal and Information Pressing, Nanjing University of Posts and Telecommunications, Nanjing 210003, China E-mail: unwoman8sohn.com
Article ID 1005-8885(2007)01-o006-06
inspective area into certain virtual grids and places the nodes into the respective grid on the basis of thek geographical information (e.g. coordinate). In every grid, the nodes will select a cluster head. Only the head has the right to communicate with other heads when the normal nodes which do not become the head fall into sleep in order to save energy. The detail of the protocol will be discussed later. Reference [3] describes a TDMA method for designing the time slot on the basis of vertex coloring algorithm. Reference [4’j describes an energy eficient protocol on the basis of controlled power with multiple transmission levels. Moreover, Refs. [5-91 also contributes certain useful ideas for MAC protocols. Reference [ 101 is beneficial to this study for cluster management. Although these protocols decrease the energy consumption in one aspect, the energy will be wasted in other aspects. Hence, it was considered to integrate the advantage of grids division in GAF and time slots division in TDMA, and finally a more efficient protocol was obtained for saving the energy assumption: A power-controlled MAC protocol associated with GAF for WSNs. It can also be referred to as GPCMAC. The remainder of this article is organized as follows: Section 2 gives the details on the related studies. Section 3 presents the study for integrating certain useful protocols and the improvement in the protocol. Simulation results and performance comparisons are shown in Sect. 4. The article is concluded in Sect. 5.
2 Relatedrkrdb Many WSN protocols have been developed in recent years. One of the earlier studies, GAF, was to select a cluster head in every grid on the basis of the node’s coordinate. In the grid, only the cluster head was awake when the other nodes fell into sleep. There are two phases in the GAF algorithm. The grid is divided in the first phase. It was assumed that the network plane is divided into virtual R X R grid (see.Fig. I). Each cell has a size r>&R, which is computed with R2 + ( 2 R ) ’ d r 2 , where r is the nominal radio range of the sensor nodes. This cell size guarantees connectivity of the whole sensor field.
No. 1
XIAO Xiao, et al.: Energy efficientTDMA-based MAC protocol associated with GAF for wireless sensor networks
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difficult to make enough nodes work in a single time slot. The advantage of vertex-coloring algorithm is not obvious.
8 A p o w e r c o n t r o ~MAC ptalocol assodatd wlth QAF for WSNs Fig. 1 Radio range in a grid
The second phase of GAF algorithm denotes the method to select the cluster head. The nodes switch the status between sleeping and working which include the status of discovery and being active. When the node wakes up, it exchanges information with the other nodes in the same grid. Then the node will know whether it has become the cluster head. Every node has three statuses, respectively, discovery, active, and sleep. All the nodes will be in the discovery status when the network is initialized. Every node has the sleep timer, discovery timer, and active timer. Depending on these timers, the nodes can have a contention for the cluster head reasonably, and switch the status in sleeping, discovery, and active status, which is selected by the cluster head. PCSMAC [4] improves the SMAC protocol on the basis of the level of multiple transmission power. It reduces the probability of data collision and overfull control information. This protocol improves the energy efficiency on the basis of different controlled power of RTS, CTS, ACK, and DATA. In general, the power of RTS, CTS, and ACK is stronger than the power of DATA because the control information should be strong enough in order to be accepted by every neighbor nodes that will fall into sleep avoiding interruption of working nodes communication. CoLaNet [3J protocol describes a vertex-coloring algorithm, which is used to divide the TDMA time slot. The nodes can communicatein an undisturbed environment because the nodes which may cause disturbance are put into a different time slot on the basis of vertex-coloring algorithm. The sensor nodes closer to each other have similar sensed data. So, if these nodes transmit the data to the father node, it will be a waste of energy and compel the father node to consume more energy when it aggregates reduplicate data. Furthermore, the SINK node that broadcasts the time slot assignment rule will increase the time slots for more transmission channels. It enhances the delay of the network. If the GAF is utilized to divide the grids, it will avoid the nodes from transmitting the reduplicate data. However, the problem also exists because the node is randomly disposed, and so certain parts of the area may contain too many nodes. The density of the nodes in this area is so huge that even the GAF is used, and the interference is still large because the size of the grid is too small. Even the vertex algorithm is used, and it is
For standing out the advantage of vertex-coloring algorithm, the power is controlled on the basis of the principle referred to in Refs. [4, 111. The time slot assignment algorithm and channel interference algorithm referred to in Ref. [3] was also improved. On the basis of the different target nodes, the transmit power dynamic was changed, and so the interfering range of the source node is diminished. It reduces the interrupting probability of “source-4estination pair”, so less time slots will be divided, and in this manner, more nodes will work in one time slot. The efficiency of every time slot is enhanced due to the improvement. The probability of data overflowing as a result of the full buffer is reduced and the delay of the network is also reduced. Moreover, owing to the reduction in transmission power, the whole sensor radio module consumes less energy. More energy will be saved for the single node and the whole network. Figure. 2 shows the protocol stacks that are divided into four phases: GAF topology establishment phase, time slot request, and broadcast phase, data sending phase, and sleeping phase. GAF Tuneslot , Data topology request and’ sending Sleeping phase establishment broadcast ’ phase phase Phase II
1
I
I
/First time slot in it
II
t/ Working phase
I
I
I
Fig. 2 GKMAC protocol stack
3.1 GAF topology establishment phase After achieving initialization, the nodes will identify their location by communicatingwith each other and the grid will be divided in virtue of the GAF rule. The SINK node which is the head of all nodes will broadcast the grid distribution result to every node on the basis of the location information which the nodes have informed to SINK node. After deciding the gridb, the nodes compete for the cluster head in their respective griil. The nodes which become head sense and transmit the data aqd the failure nodes fall asleep when their sense modules keep working. When the sleep timer reaches timeout, the sleepy node transfer competes for the cluster head again. But the competition for head is a random action. The process may interrupt the time slot for data transmission which has been assigned by the SINK node, so the protocol assigns a unique time slot to compete for the cluster head. The competition time slot is assigned to every node as the
The Journal of CHUPT
8
first time slot in the protocol stack which has been described in Fig. 2. Zn this manner, the current cluster head will stop the transmission of data to other heads in the first time slot, and it will participate in the competition for the head in its own grid. Now, the problem is how to make the sleepy node master the moment fmt time slot start at. The current head node is easy to know when the first time slot starts because of the SINK node's broadcasting, but the sleepy nodes are difficult to identify when the fmt time slot starts because they cannot receive the broadcast message from the SINK node. For this reason, every sleepy node is compelled to hear a little time when they wake up. Until the SINK node broadcasts the new time slot assignment, all nodes will compete for the head in the new first time slot. Original GAF algorithm requires that the nodes participate in the head competition immediately when they wake up. But, it is easy to cayse data collision. Hence, the protocol delays a little time for the nodes which is not the head to ensure no interference for data delivery ratio. In the simulation, it was found that it did not affect the delay in performance. So,it is reasonable for selecting the cluster head. 3.2 Time slot request and broadcast phase
The cluster head in every grid will inform their sending request to the SINK node in this phase, and then the SINK node will decide the time slot division as the following algorithms and broadcast the decision to every head on the basis of their node ID and grid ID. 3.2.1 Decide the least transmission power
In Refs. [4, 111, the author provides certain equations to calculate the least transmission power. There are four equations as folIows:
p =-44
" P ,
(3)
Pm=-C 44 (4) P, where P is the transmission power, A is the carrier wavelength, n is the path loss coefficient, Gt is the transmitter antenna gain, and G, is the receiver antenna gain. The value of n is usually between 2 and 6 depending on the physical environment. In order to provide the minimum necessary received signal strength index (RSSI) for the reception of a frame; the minimum transmission power level P, at the source node is calculated as Eq.(2). Rt is the w i v e d power when the source node transmits with P,. By combining Eqs. (1) and (2), Eq. (3) is obtained, in
2007
order to cope with the inaccurate estimation of the channel fading characteristic, the calculated P, can be multiplied by a preset coefficient C as in Eq. (4). If a receiver node knows the transmission power level used by the sender node Pt, with a known R,, and measuring the power level for the received frame Pr,it is possible for the receiver node to calculate the minimum required transmission power level P, to send a frame back to the source node using EQ.(4). 3.2.2 Time slot assignment algorithm
The slot assignment algorithm referred to Ref. I31 is introduced, and in a word, there are three conditions (on the assumption that '' a -+ b " represents the link between node a and node b, the rest communication links may be deduced by analogy): 1) a + c and b + c cannot exist in the same time slot 2) a + b and a -+ c cannot exist in the same time slot, too. 3) When a + b interferesc -+ d , the two links cannot exist in the same time slot, and vice versa. The links which cannot exist in the same time slot are looked upon as the points which cannot color up the same color. The vertex-coloring algorithm can be used to color up every communication link. The link which colors up the same color can be taken into the same time slot. That means the number of colors determine the number of time slots. 3.2.3
Channel interference algorithm
The third condition in the time slot assignment algorithm refers to the channel interference algorithm, and the protocol predigests it. Because of the control to the source node's transmission power, every source node reduces its range of interference, which basically equals the distance between the source and the destination. So, the algorithm that was used (was on the assumption that the distance between node a and node b is described as ab, the rest distance may be deduced by analogy): if one of the four conditions which are a b 3 a d , a b 3 ac, cd3cb, c d 3 c a come into existence, the link a + b and link c + d interfere with each other, and hence cannot exist in the same time slot. 3.2.4 The fungible slgorithm for the accurate vertexcoloring algorithm A fungible algorithm needs to be selected for the accurate
vertex-coloring algorithm because it is too complex and every node's computational capacity is restricted in the simulation environment or in the actual environment. So, it was decided to use the Powell algorithm referred to in Ref. [12] to replace the accurate vertex-coloring algorithm. The concrete description is described as follows: 1) Every node in graph G is arrayed on the basis of the descending order of the degree which means the numbers
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XIAO Xiao, et al.: Energy efficient TDMA-based MAC protocol associated with GAF for wireless sensor networks
which are linked to the node itself: 2) Then one node is colored up with another color and another node is colored up with the same color which is not the neighbor to the former that has been colored up: 3) The second color is used to color up the node which has not been colored up by repeating 2). Then the third color is used to carry through the similar action. The process is complete only when all the nodes have been colored up. 3.3 Data sendlng phase Every node will transmit the data without collision, competition and overhear in the time slot which is divided on the basis of the above-mentioned algorithm. The energy consumption is smaller compared to CoLaNet protocols when the nodes transmit the same amount of data because of smaller transmission power. The energy consumption is divided into two parts. One is the consumption in the radio module; the other is used for the working of the internal circuit. In the simulation, the internal consumption is set to a constant value, and the consumption in the radio module is set to a variable which is altered with the transmission power. 3.4 Sleeplng phase
The sleeping phase follows the working phase. The node moves to the working phase (discovery status) automatically when the sleep timer reaches timeout. Considering that the node may become a failure and so new nodes may be deployed in the networks, the topology of the network may be altered; moreover, the amount of the data will also be variable. So, the transmission power and the time slot should be recomputed after a fixed time. Reference [13] proposes to utilize a scheme to broadcast for setting up a phase-switching schedule against establishing a constant time slot assignment in the network and design a reasonable time slot allocation mechanism on the basis of the traftic strength and unsuccessful transmission rate. This adaptation issue is an ongoing effort and is beyond the scope of this study.
9
“CoLaNet” and the “Normal TDMA” associated with GAF are also simulated. NS2 introduced in Refs. [14-151 was used to achieve the simulation. The network includes 50 nodes in 500 mX500 m square area. Figure. 3 shows total energy consumption of 6 instances. GPCMAC shows that the total energy efficiency is better than other protocols and the lifetime is also longer. Energy analysis
/
Timds
Fig. 3 Energy assumption
Nine groups of simulations were processed on the basis of the different numbers of nodes and different sizes of square area for the performance of end-to-end delay which is defined as:
where Ed ,T, ,T, , and Ns, respectively, denote end-to-end delay, time for receiving packets, time for sending packets, and the number of sending packets. The fist group has 5 nodes in 50 mX50 m square area, the second group has 10 nodes in 100 mX 100 m square area, the rest may be deduced by analogy until the ninth group has 45 nodes in 450 m x 450 m square area. Figure 4 shows the Normal TDMA that shows the worst delay performance. CoLaNet’s delay performance is similar to the PCMAC. The GPCMAC used for this study has the best delay performance.
4 Slmulatlonrerults The protocol that is described is entitled “A power controlled MAC protocol associated with GAF‘ and it will be termed “GPCMAC” for short in the simulation. The “power controlled MAC protocol without GAF” is short for “PCMAC” to compare GPCMAC. Reference [3] refers to the CoLaNet that is expressed to “CoLaNet” in the simulation. Moreover, an original TDMA protocol is still used which denotes the number of nodes, number of time slots, and is expressed as ‘‘Normal TDMA” in the simulation. For an all-round comparison, The
*GPCMAC
Node numbers
Fig. 4 Delay performance
In Fig. 5, the performance of three different MAC protocols
The Journal of CHUPT
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(GPCMAC, PCMAC, and C o m e t ) is compared in terms of the average delivery ratio of the data packets. Delivery ratio symbolizes the reliability of the network. It is defined as:
where, 0, $, and T, , respectively, denote delivery ratio, number of received packets, and number of transmitted packets. 1.Ooo
R
GetRatio analysis
0.999
.-0
0.999
E2. 0.998 0
'I
.z 0.998 0
*
$u 0.997
4
0.997
4-PcuAc -coLaNel -r GPCMAC
"I
0.9%05
10
15
25 30 Node numbers
20
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40
45
International Conference on Mobile Computing and Networking (MobiCOM 2001), Jul 16-21,2001, Rome, Italy. 2001: 70-84 2. Le Xuan Hung, Seo Dae Hong, Lee Sungyoung, et al. Minimum-energy data dissemination in coordination based sensor networks. Proceedings of 11th IEEE International Conference on Embedded and Real-time Computing Systems and Applications (RTCSAM), Aug 17-19, 2005, Hong Kong, China. Piscataway, NJ, USA: IEEE Computer Society, 2005: 381-386 3. Chou Cheng-fu, Chuang Kwang-ting. CoLaNet: cross-layer design of energy effiicient wireless sensor networks. Proceedings of the 2005 Systems Communications (ICW'OS), Aug 14-17, 2005, Montreal, Canada. Piscataway, NJ, USA. IEEEComputer Society, 2005: 304-369 Nar P C, Cayirci E. PCSMAC: a power controlled sensor-MAC protocol for wireless sensor networks. Proceedings of 2nd European Workshop on Wireless Sensor Networks, Jan 3 1-Feb 2, 2005, Istanbul, Turkey. Piscataway, NJ, USA EFB Computer Society, 2005: 81-92 Bao L, Garcia-Luna-Aceves J J. A new approach to channel scheduling for Ad-hoc networks. F'roedm . gs of 7th Annual International Conference on Mobile Computing and access
Fig. 5 Delivery ratio performance
The performance of GPCMAC decreases in some sort than other two protocols, but the difference is not obvious and can be ignored.
In this study, GPCMAC has been introduced, a power controlled MAC protocol associated with GAF for wireless sensor networks. This scheme is on the basis of GAF protoco1,vertexcoloring algorithm, and the minimal transmission power for saving energy and prolonging network lifetime. Vertex-coloring algorithm and minimal transmission power were employed to decide the least time slots in the network. The simulation shows that GPCMAC is successful in meeting the design goals of energy efficiency, good performance of delivery ratio, and end-to-end delay. The simulation also shows that the protocol increases the network lifetime successfully than other approaches, especially with high node density. Acknowledgements This work is supported by the National Natural Science Foundation of China (60372107) and Chongqing Key Laboratay Open Project Foundation.
References 1.
Xu Y, Heidemam J, Estrin D. Geography informed energy conservation for Ad-hoc routing. Proceedings of 7th Annual
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Networking (MobiCOM 2001), Jul 16-21, 2001: Rome, Italy. 2001: 210-221 6.
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Rajendran V, Obraczka K, Garia-Luna-Aceves J J. Energy efficient, collision-fke medium access control for wireless sensor networks. Proceedings of 1st International Conference on Embedded Networked Sensor System (SenSys'O3), Nov 5-7, 2003, Los Angeles, CA, USA. New York, NY, USA: ACM press, 2003: 181-192 Lu G, Krishnamachari B, Raghavendra C. An adaptive energy efficient and low-latency MAC for data gathering in wireless sensor networks. proceedings of International Paralled and Distributed Processing Symp (JPDPS'M), Vol 18, Apr 26-30, 2004, Santa Fe, NM, USA. Los Alamitos, CA, USA IEEE Computer Society, 2004: 3091-3098 Cui Shu-guang, Madan R, Goldsmith A, et al. Joint routing. MAC, and link layer optimization in sensor networks with energy constraints. Proceedings of International on Communications: Vol 2, May 16-20,2005, Seoul, South Korea. Piscataway, NJ USA: IEEE,2005: 725-729 Sun Li-min, Li Jian-zhong, Chen Yu, et al. Wireless sensor networks. Beijing, China: Tsinghua University Press, 2005 (in Chinese)
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Ho Shen-ben, Su Xiao. CuMPE cluster management and power efficient protocol for wireless sensor networks. Proceedings of 3rd International Conference on Information Technology Research and Education, Jun 27-30, 2005, Taipei, China. Piscataway, NJ, USA IEEEComputer Society, 2005: 60-67 11. Liu Guo-pei Madun-Jie. Radio and antenna. Changsha, China: National Defence & Science and Technology University Press,
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2004 (in Chinese) 12. Xiao Wei-shu. Graph theory and its algorithm. Beijing, China: Aviation Industry Press, 1993 (in Chinese) 13. Ren Qing-chun, Liang Qi-lian. An energy eficient MAC protocol for wireless sensor Networks. Proceedings of Global TelecommunicationsConference: Vol 1, Nov 28-Dec 2, 2005, St Louis, MO, USA. Piscataway, NJ, USA: IEEE,2005: 5 14. Xu Lei-ming, et al. NS and networking simulation. Beijing, China: Posts and Telecom Press. 2003 (in Chinese) 15. Wang Hai-tao,Zheng Shao-ren. Routing protocols for Ad-hoc network & their performance comparisons. The Journal of Chongqing University of Posts and TelecommunicationsNatural Science, 2002, 14(4): 73-77 (in Chinese) Biogcaphies:XIAO Xiao, from Jiangsu Province, master Candidate, Nanjing University of Posts
and Telecommunications, interested in the research on signal processing, wireless sensor networks, mobile communication.
11
ZHENG Bao-yu, from Fujian Province,professor,
doctoral supemisor, Department of Information, Nanjing University of Posts and Telmmmunications, interested in the research on intelligence signal pmcessing, communication signal processing, and q u a n u tm signal pmesing, etc.
YAN Zhen-ya from Fujian Province, Ph. D. Candidate, Nanjing University of Posts and TelecommUnications, intemted in wireless sensor network, particle filter, cooperative diversity, etc.
CHEN Chao, from Jiangsu Province, master Candidate, Nanjing Univexsity of Posts and Telecommunications, interested in the research on signal processing, mobile Cwrmmunicaeion.