Dae-young Kim

Jinsung Cho

English

IntechOpen

Selection of our books indexed in the Book Citation Index in Web of Science™ Core Collection (BKCI)Interested in publishing with us? Contact book.department@intechopen.comNumbers displayed above are based on latest data collected. For more information visit www.intechopen.comOpen access books availableCountries delivered to Contributors from top 500 universitiesInternational  authors and editorsOur authors are among themost cited scientistsDownloadsWe are IntechOpen,the world’s leading publisher ofOpen Access booksBuilt by scientists, for scientists12.2%122,000 135MTOP 1%1544,800A Reliable and Flexible Transmission Method in Wireless Sensor Networks 229A Reliable and Flexible Transmission Method in Wireless Sensor NetworksDae-Young Kim and Jinsung Cho0A Reliable and Flexible TransmissionMethod in Wireless Sensor NetworksDae-Young Kim and Jinsung ChoKyung Hee UniversityS. Korea1. IntroductionRecent advances in wireless communication have enabled multifunctional tiny nodes to con-struct a wireless network by themselves Akyildiz et al. (2002). The network is called a wire-less sensor network. The tiny sensor nodes are densely deployed in a physical space. Theymonitor physical phenomena, deliver information, and cooperate with neighbor nodes Aky-ildiz et al. (2002); Culler et al. (2004); Hac (2003); Zhao and Guibas (2004); Chong and Kumar(2003). The communication systems in end-to-end data transmission of wireless sensor net-works employ a recovery mechanism for lost data during data transmissions because reliabledata transmissions are required for various sensor network applications.Two types of retransmission have been proposed for the recovery, namely end-to-end lossrecovery (E2E) and hop-by-hop loss recovery (HBH). In these mechanisms, lost packets areretransmitted from a source node or an intermediate node. If a retransmit request for lostpackets is sent to a source node, the end-to-end delay may increase because channel erroraccumulates exponentially over multi-hops Wan et al. (2002). The well-known HBH mecha-nisms are PSFQ Wan et al. (2002) and RMST Stann & Heidemann (2003). PSFQ is based onACKmessage and RMST is on NACKmessage. In HBH, when intermediate nodes cache datapackets into storage, retransmissions can be requested to an intermediate relay node to reduceend-to-end delays. Because sensor nodes have limited resources, however, it is difficult for allsensor nodes to find sufficient space in their routing paths to cache data packets. There istherefore a tradeoff between end-to-end delays and memory requirements.Because data traffic on sensor networks requires a variety of levels of communication reliabil-ity (CR) depending on the application, a loss recovery method to guarantee the desired CRshould be provided. Traditional loss recovery mechanisms consider only 100% reliability. Inthis letter, we propose a flexible loss recovery mechanism to guarantee various CRs and wediscuss the tradeoff between end-to-end delays and memory requirements for various CRs.The proposed method can be widely used for the design of wireless sensor networks thatrequire a variety of CRs.2. A Reliable and Flexible Transmission Method in Wireless Sensor Networks:Active CachingAsmentioned previously, E2E involves large end-to-end delays for 100% reliability because ofhigh packet loss during multi-hop transmissions. To guarantee high reliability and minimal13www.intechopen.comSmart Wireless Sensor Networks230RELIABLE − TRANSMIT(CR, i, pi , Ptx(i − 1), F(i − 1))1. Ptx [i] ← Ptx [i − 1] · (1− pi)2. if Ptx [i] > CR3. then F[i] ← f alse4. else F[i] ← true5. Ptx [i] ← (1− pi)6. cache data packets to a node niFig. 1. Active caching algorithm at i-th node, ni.Fig. 2. An example of active caching.end-to-end delays, HBH caches data in every node over a routing path resulting in large mem-ory requirements. When only some nodes cache data on a routing path, there exists a tradeoffbetween the end-to-end delays and the memory requirements. For applications which donot require 100% reliability, every node needs not cache data via HBH. When a target CR isgiven, we need a flexible method to guarantee the given CR while minimizing the memoryrequirement. In this section, we present such a method - active caching (AC).The proposed scheme allows various CRs of application services. It determines positionswhere data caching occurs using a dynamic programming algorithm, which solves every sub-problem just once and then saves its answer in a table to avoid the work of recomputing theanswer Cormen et al. (2001). If there are holes in sequence numbers of received data, a cachingnode recognizes packet loss Karl & Willig (2005). The caching node sends a NACK messageto a previous caching node along the path and the previous caching node retransmits lostpackets selectively.First, we define the problem and subproblems for the active caching as a dynamic program-ming algorithm to guarantee an end-to-end reliable data transmission as:Problem: Ptx(H) > CR.Subproblem: Ptx(h) > CR, where h = 1, 2, · · · , H.The packet delivery rate Ptx(H) during total hop counts H should be greater than the desiredcommunication reliability CR. To do that, the packet delivery rate Ptx(h) during hop counts hin each hop should be greater than the CR. The key idea for solving the problem is to cachedata packets if the probability of packet transmission does not satisfy the desired communi-cation reliability. By solving the subproblems, we can solve the entire problem.www.intechopen.comA Reliable and Flexible Transmission Method in Wireless Sensor Networks 231Figure 1 shows the proposed active caching algorithm for loss recovery. Each node solves thesubproblem using the tables for the packet delivery rate Ptx(i) until i-th hop and the cachingflag of i-th node F(i). Both Ptx(i− 1) and F(i− 1) of the tables are piggybacked in data packetsand they are delivered to the next node. In a source node (i = 1), Ptx(1) is 1 − p1 as thepacket delivery rate at the 1st hop and F(1) is true. Line 1-3: ni calculates Ptx(i) using Ptx(i −1), where Ptx(i) accumulates the packet delivery rate 1 − pi of i-th hop while packets aretransmitted. After that, it compares Ptx(i) with CR. If Ptx(i) satisfies the desired CR, ni isnot a caching node (F(i) is f alse). Line 4-6: If Ptx(i) does not guarantee the desired CR, nibecomes a caching node (F(i) is true). In this case, Ptx(i) compensates for its packet deliveryrate as the reliability instead of accumulating Ptx(i) and data packets are cached onto ni’sbuffer. Each node runs the algorithm of Figure 1 and the total active caching over a routingpath is performed by the dynamic programming algorithm. Figure 2 shows an example of theactive caching when seven sensor nodes are deployed sequentially and they have an average5% packet loss rate and 80% CR. Every node satisfies 80% CR and data caching occurs at n5.When packet loss happens between a source node n1 and the caching node n5, the cachingnode requests retransmission to the source node. When packet loss happens between thecaching node and a destination node n7, the destination node requests retransmission to thecaching node.3. AnalysisA packet loss rate occurs due to wireless link and contention errors. Since all the packets aredestined to the sink node in wireless sensor networks, the contention error in links close tothe sink node may increase. To model the packet loss rate at i-th hop, we assume the uniformlink error pl and the contention error which is proportional to the square of transmission hopcounts.pi = pl + αi2, (1)where α is the contention failure factor. Then the packet delivery rate during h hops from thes-th node isPtx(s, h) =s+h−1∏i=s(1− pi). (2)Data caching occurs when Ptx(s, h) is lower than CR. When the number of nodes N over aroute and CR are given, the hop counts h from a caching node s and the number of cachingnodes Nc are obtained by the function in Figure 3. Φ represents a set of (s, h) tuples and the(s, h) tuples are used to compute the retransmission counts of lost packets. For example inFigure 2, Φ = {(1, 4), (5, 2)}.Φ = {(sj, hj) | j = 1, · · · , NC}. (3)If the retransmission counts for h hops from a caching node s is given by ψ(s, h), the totalretransmission counts E[C] between a source node and a sink node are represented by thesum of ψ(s, h) asE[C] =Nc∑j=1ψ(sj, hj). (4)Because the retransmitted packets can also experience transmission failure, we should con-sider repeated retransmissions for ψ(s, h). Let Γ f (j, s, h) indicate the number of transmittedpackets at the j-th retransmission. Then ψ(s, h) can be represented aswww.intechopen.comSmart Wireless Sensor Networks232CalcHopCounts(N,CR)1. n ← 1, s ← 1, h ← 1, Nc ← 02. Φ = φ3. loop: n < N4. if Ptx(s, h) > CR5. then n ← n + 1, h ← h + 1 //no caching6. else h ← h − 1 //caching7. if (h = 0)8. then h ← 1, n ← n + 19. add (s, h) to Φ, Nc ← Nc + 110. s ← n, h ← 111. end loop12. if (h > 1)13. then add (s, h − 1) to Φ, Nc ← Nc + 1Fig. 3. Function to obtain (s, h) tuples.ψ(s, h) =∞∑j=1(h · Γ f (j, s, h) · Ptx(s, h)). (5)If we let Γs(k, s, h) be the number of successfully transmitted packets among k packets duringh hops from node s, Γ f (j, s, h) can be represented recursively asΓ f (j, s, h) = Γ f (j − 1, s, h)−[Γs(Γ f (j − 1, s, h), s, h)]1, (6)where Γ f (0, s, h) = K and K is the number of total packets which is generated in a sourcenode.The number of successfully transmitted packets Γs(k, s, h) can be calculated by the probabilityof successful transmission of Bernoulli trials Ps(k,m, s, h) asΓs(k, s, h) =k∑m=1m · Ps(k,m, s, h). (7)If m data packets are transmitted successfully among k packets to deliver across h hops from acaching node s, the probability of successful transmissions can be obtained by Bernoulli trialsasPs(k,m, s, h) =(km)· Ptx(s, h)m·(1− Ptx(s, h))k−m. (8)The memory requirement B is defined as the caching rates of intermediate nodes including asource node. It is computed by Nc and the number of relay nodes over a routing path:E[B] =NcN − 1. (9)1 [x] is n, in case of n − 0.5 ≤ x < n + 0.5www.intechopen.comA Reliable and Flexible Transmission Method in Wireless Sensor Networks 233Fig. 4. Validation of our analysis (p=0.03).A high E[C] indicates large end-to-end transmission delays and E[B] represents the memoryrequirements of buffers on the data transmission routes. Because both E[C] and E[B] can beestimated by CR of traffic through Eq.(4) and Eq.(9), a flexible data transmission system canbe designed.4. EvaluationIn this section, we validate the analysis through simulations and compare the performance ofactive caching (AC) with that of E2E andHBH. For the simulation, we assume 20 sensor nodesare deployed sequentially and the wireless channel has both link and contention error as de-scribed in Section 3. The contention failure factor α is determined as 0.0001 by consideringtotal hop counts. So, pi in Eq.(1) ranges from 0.03 to 0.07 when p is 0.03 in our experiments.The sensor nodes employ AODV as a routing protocol. Assuming a packet is 30 bytes andthe data rate is 250kbps, we perform the analysis and simulation by varying CR from 10% to100%. AC with CR from 0.1 to 1 is expressed as AC0.1 to AC1.Figure 4 shows the results of the analysis and the simulation of the retransmission counts andthe memory requirements when a source transmits 40 packets. The results of the analysisand the simulation show an average of 94% similarity. Figure 4 also represents the tradeoffas mentioned earlier. The high CR requires a high memory requirement for reliability and itdecreases the retransmission counts. When thememory requirement is the lowest, the retrans-mission counts are the highest and AC runs as E2E. In short, we can design wireless sensornetworks that take the desired CR and memory requirements into consideration through theproposed active caching.Figure 5 shows the performance comparison of E2E, HBH, and AC. Because AC with thehighest memory requirement caches data to every intermediate node, it operates as HBH.When AC does not perform data caching, it operates as E2E. That is, AC switches betweenHBH and E2E while showing the performance tradeoff between them. In addition, it has atolerable end-to-end delay to minimize the memory requirement depending on CR. In Fig-ure 5, the end-to-end delays of E2E increase when the wireless channel has a high link errorrate. However, the end-to-end delay of AC maintains similar values because AC increases thememory requirements to ensure CR. An evaluation has been performed for 10 and 50 nodeswww.intechopen.comSmart Wireless Sensor Networks234deployed over a route, and the results are similar to the case of 20 nodes. These results havebeen omitted due to the page limitation.Figure 6 shows the ratio of caching nodes over relay nodes. Because the contention errorincreases when the density of nodes increases, the ratio of caching nodes increases when thenumber of sensor nodes increases.Fig. 5. Performance comparison of E2E, HBH, and AC.Fig. 6. The ratio of caching nodes.5. ConclusionWireless sensor networks transmit data through multiple hops. End-to-end data transmissionmust recover lost data for reliable data transmissions. Active caching (AC) provides moreflexible end-to-end delays and memory requirements for a given reliability than the existingrecovery mechanisms (i.e., E2E, HBH). By using the proposed dynamic loss recovery withactive caching, a flexible end-to-end data transmission system can be designed.www.intechopen.comA Reliable and Flexible Transmission Method in Wireless Sensor Networks 2356. AcknowledgementThis research was supported by the MKE(The Ministry of Knowledge Economy), Korea, un-der the ITRC(Information Technology Research Center) support program supervised by theNIPA(National IT Industry Promotion Agency)" (NIPA-2010-(C1090-1021-0003))7. ReferencesAkyildiz, I. F., Su, W., Sankarasubramaniam, Y., and Cayirci, E. (2002). A survey on sensornetworks, IEEE Communications Magazine, Vol. 40(No. 8): pp. 102–114, August 2002.Culler, D., Estrin, D., and Srivastava, M. (2004). Guest editors’ introduction: Overview ofsensor networks. IEEE Computer, Vol. 37(No. 8): pp. 41–49, August 2004.Hac, A. (2003). Wireless sensor network designs, John Wiley & Sons, 2003.Zhao, F. and Guibas, L. (2004). Wireless sensor networks: An information processing approach,Morgan Kaufmann Publishers, 2004.Chong, C. -Y. and Kumar, S. (2003). Sensor networks: Evolution, opprtunities, and challenges,Proceedings of the IEEE, Vol. 91(No. 8): pp. 1247-1256, August 2003.Wan, C. Y., Campbell, A. T., and Krishnamurthy, L. (2002). PSFQ: A reliable transport protocolfor wireless sensor networks, Proceedings of ACM International Workshop on WirelessSensor Networks and Applications, pp. 1-11, September 2002.Stann, F. and Heidemann, J. (2003). RMST: Reliable data transport in sensor networks, Pro-ceedings of IEEE International Workshop on Sensor Network Protocols and Applications,pp. 102-112, May 2003.Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. (2001). Introduction to Algorithms,Vol. 1, The MIT Press, 2001.Karl, H. and Willig, A. (2005). Protocols and architectures for wireless sensor networks, John Wiley& Sons, 2005.www.intechopen.comwww.intechopen.comSmart Wireless Sensor NetworksEdited by Yen Kheng TanISBN 978-953-307-261-6Hard cover, 418 pagesPublisher InTechPublished online 14, December, 2010Published in print edition December, 2010InTech EuropeUniversity Campus STeP Ri Slavka Krautzeka 83/A 51000 Rijeka, Croatia Phone: +385 (51) 770 447 InTech ChinaUnit 405, Office Block, Hotel Equatorial Shanghai No.65, Yan An Road (West), Shanghai, 200040, China Phone: +86-21-62489820 Fax: +86-21-62489821The recent development of communication and sensor technology results in the growth of a new attractive andchallenging area â€“ wireless sensor networks (WSNs). A wireless sensor network which consists of a largenumber of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with theability of wireless communication and intelligent computation, these nodes become smart sensors which do notonly perceive ambient physical parameters but also be able to process information, cooperate with each otherand self-organize into the network. These new features assist the sensor nodes as well as the network tooperate more efficiently in terms of both data acquisition and energy consumption. Special purposes of theapplications require design and operation of WSNs different from conventional networks such as the internet.The network design must take into account of the objectives of specific applications. The nature of deployedenvironment must be considered. The limited of sensor nodesâ€™ resources such as memory, computationalability, communication bandwidth and energy source are the challenges in network design. A smart wirelesssensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage,reliability and security of networkâ€™s operation for a maximized lifetime. This book discusses various aspectsof designing such smart wireless sensor networks. Main topics includes: design methodologies, networkprotocols and algorithms, quality of service management, coverage optimization, time synchronization andsecurity techniques for sensor networks.How to referenceIn order to correctly reference this scholarly work, feel free to copy and paste the following:Jinsung Cho and Dae-young Kim (2010). A Reliable and Flexible Transmission Method in Wireless SensorNetworks, Smart Wireless Sensor Networks, Yen Kheng Tan (Ed.), ISBN: 978-953-307-261-6, InTech,Available from: http://www.intechopen.com/books/smart-wireless-sensor-networks/a-reliable-and-flexible-transmission-method-in-wireless-sensor-networkswww.intechopen.comFax: +385 (51) 686 166www.intechopen.comFax: +86-21-62489821© 2010 The Author(s). Licensee IntechOpen. This chapter is distributedunder the terms of the Creative Commons Attribution-NonCommercial-ShareAlike-3.0 License, which permits use, distribution and reproduction fornon-commercial purposes, provided the original is properly cited andderivative works building on this content are distributed under the samelicense.

A Reliable and Flexible Transmission Method in Wireless Sensor Networks

http://www.intechopen.com/chapter/pdf-download/12453

A Reliable and Flexible Transmission Method in Wireless Sensor Networks

Abstract

Similar works

Full text

Available Versions

IntechOpen