A MIXED TRANSMISSION STRATEGY TO ACHIEVE ENERGY BALANCING IN WIRELESS SENSOR NETWORKS

ABSTRACT

In this paper, we investigate the problem of energybalanced data collection in wireless sensor networks, aiming tobalance energy consumption a all sensor nodes during thedata propagation process. Energy balanced data collection canpotentially save energy consumption and prolong network lifetime,and hence it has many practical implications for sensor networkdesign and deployment. The traditional hop-by-hop transmissionmodel allows a sensor node to propagate its packets in a hop-byhopmanner towards the sink, resulting in poor energy balancingfor the entire network. To address the problem, we apply a slicebasedenergy model, and divide the problem into inter-slice andintra-slice energy balancing problems. We then propose a probabilitybasedstrategy named Inter-slice Mixed Transmission protocol andan Intra-slice Forwarding technique to address each of the problems.We propose an Energy-balanced Transmission Protocol by combiningboth techniques to achieve total energy balancing. In addition, westudy the condition of switching between inter-slice transmissionand intra-slice transmission, and the limitation of hops in intraslicetransmission. Through our extensive simulation studies, wedemonstrate that the proposed protocols achieve energy balancing,prolong network lifespan, and decrease network delay, compared withthe hop-by-hop transmission and a cluster-based routing protocolunder various parameter settings.

EXISTING SYSTEM:

Wireless sensor networks have received extensive research fortheir great potentials in a wide range of applications, such asenvironmental monitoring, event detection, structural monitoringand localization and tracking.The energy balancing problem in wireless sensor networkswas first introduced, which studies the energy balancingproperty, and proposed an energy-balanced algorithm for sortingin wireless sensor networks. Inspired by this work, several worksextend to study the energy balance problem in data propagation,based on the slice-based network model as same as our work., the authors proposed a slice-based transmission protocol withtwo strategies: nodes send data directly to the sink, and nodes forwarddata to the next slice. The ratios between the two strategies’periods are computed aiming to balance energy consumption of allnodes. Similar with precisely estimates the probabilitiesof directly sending and one-hop transmission. A closed form isderived for these probabilities under certain assumptions. Differentfrom, an adaptive distributed algorithm is proposedby, without priori knowledge of data generation rates. Astochastic estimation method is used to infer the values fromobservations of event occurrence, which can deal with networkchanges. All the above works make an assumption that each nodein the network can only propagate data packets by direct transfer orhop-by-hop transmission. Different from these works, our mixedinter-slice transmission allows each node to adjust its transmissionrange, which is more realistic and practical. The overhead ofpower control is mainly introduced by two ways. The first typeof overhead is incurred by the sink broadcasting the probabilitydistribution of sending packets between different slices to eachsensorthe network, and thus can be ignored. The second type of overheadis incurred by storing the probability distribution and the remainedenergy of one-hop neighbors on each sensor.The authors in prove that all the slices should have the samewidth to minimize the total energy spent on routing. They considerthe condition that transmission range is fixed and propose a modelwith uneven sizes of slices to balance energy consumption asensors in different slices. Wu et al.propose suboptimalalgorithms based on nonuniform deployment schemes to solve theproblem of uneven energy consumption. However, these schemesincrease the difficulty to deploy such sensor networks. Similar with, we provide a more comprehensive solution to achieve bothinter-slice and intra-slice energy balancing. In addition, we alsoanalyze the necessary condition to achieve total energy balancingfor two representative sensor network topologies.

PROPOSED SYSTEM:

In our work, we have made somesimplifying assumptions. However, real-world sensor networks aremore complex and we may encounter a few issues, which mayhave a non-negligible impact on our approach. The main issuesare as follows._ Node failure. We have assumed that a sensor node is alwaysworking until its power is depleted. In the real world, however,a node may fail for other reasons, e.g., hardware problem,physical damage and unexpected isolation by a metal cover.Unexpected node failures may reduce the balance level of thepower consumptions of sensor nodes, which in turn decreasethe eventual network lifetime. This issue becomes even worsewhen the failed nodes form geographical clusters._ Time synchronization. Our work assumes that all sensor nodesare time synchronized. Although a few time synchronizationprotocols can be used in the implementation, the resultingtime synchronization level may not be perfect. In other words,the local clocks of some nodes may largely differ from thetrue clock. As a result, it is possible that the unsynchronizedsensor nodes may fail to find the next hop for transferringpackets towards to the sink. This would reduce the networklifetime._ Identical initial energy levels. We also assume that the initialenergy levels of all sensor nodes are the same. However,this may not be true. The actual energy levels differ fromeach other. This would make the balance level of the wholenetwork even worse.In response to these issues that may be encountered in a realsensor network, our future work would explore such issues in moredetail and will propose measures to tackle these issues.

CONCLUSION

In this work, we study the energy balancing problem fordata collection in wireless sensor networks. By using a slicebasedmodel, we address the problem by solving both inter-sliceand intra-slice energy balancing. We propose an Energy-balancedTransmission Protocol by combining both the inter-slice mixedtransmission strategy and the intra-slice forwarding technique toachieve overall energy balancing in sensor networks.In the analysis of inter-slice energy balancing, we discover thatto achieve inter-slice energy balancing, the transmission range ofa sensor node should be large enough with respect to the sensornetwork size, and they should satisfy the necessary condition wederive. However, there always exists a trade-off between betterenergy balancing performance and the cost of sensor networkdeployment (i.e., using less expensive sensors with a shortertransmission range).

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