Impact of Limiting Number of Links on the Lifetime of Wireless Sensor Networks

2014 10th International Conference on Communications (COMM)

2014

Self Cite

Wireless Sensor Networks (WSNs) comprising of battery-powered sensor nodes are being used in a wide range of applications. The feasibility of such applications is highly influenced by the longevity of these networks. In this work, we present a realistic WSN lifetime optimization framework where transmission power levels for both data and ACK packets are optimally selected (i.e., a complete link-layer handshaking cycle is modeled). Log-normal shadowing path loss model is employed to take into account the effects of path losses. We utilized the developed Mixed Integer Programming (MIP) based optimization framework to investigate the impact of data packet length on WSN lifetime. To quantify the effects of data packet length on network lifetime we explored the parameter space consisting of the number of nodes and node deployment density. Our results show that the optimal data packet length is the maximum allowed length.

Section: Background On Mathematical Programmingmentioning

confidence: 99%

Data packet length optimization for Wireless Sensor Network lifetime maximization

Akbaş

Yildiz

2014 10th International Conference on Communications (COMM)

2014

Self Cite

“…Bicakci et al [3] present an LP framework to guide designers in effectively using critical trade-offs for prolonging network lifetime. Tavli et al [14] investigate the optimal number links per sensor node to achieve maximal network lifetime by using a Mixed Integer Programming (MIP) framework. In [16] a novel LP framework is introduced to model sensor network lifetime when data reduction through compression is utilized.…”

Section: Related Workmentioning

confidence: 99%

“…The constraint equations (2) to (14) depict the contextual privacy and data compression frameworks detailed in Section 3. In this framework, we used the energy model introduced in [6], where the amount of energy to transmit a bit is represented as Ptx,ij = ρ + εd α ij , and the amount of energy to receive a bit is represented as Prx = ρ, where ρ models the energy dissipation on electronic circuitry, ε denotes the transmitter's efficiency, α represents the path loss exponent and dij is the distance between node-i and node-j.…”

Section: Lp Modelmentioning

confidence: 99%

“…• If the distance between nodes is larger than the maximum transmission range of the node then the data flow is zero between these nodes for the transmitted raw and compressed data, respectively (transmission range limit) -Equation (13) and Equation (14). These constraints come from the contextual privacy topology model described in Figure 1.…”

Section: Lp Modelmentioning

confidence: 99%

See 1 more Smart Citation

Prolonging wireless sensor network lifetime in stealth mode through intelligent data compression

Zilan

Ozdemir

Proceedings of the 10th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, &Amp; Ubiquitous Networks

et al. 2013

Self Cite

In certain surveillance applications it is imperative that the deployed Wireless Sensor Network (WSN) is not detected by the adversaries before the intruding party is detected by the WSN (i.e., the WSN is in the stealth mode of operation). Limiting the transmission ranges of sensor nodes is an option to mitigate the compromising privacy of the WSN (i.e., data communication within the WSN is not detected from far away). However, using all sensor nodes with minimal energy transmission level has devastating effects on the network lifetime because some nodes acting as relays are heavily burdened by conveying the data flowing from an unproportionately high number of sensor nodes. Such an approach will lead to the premature death of certain subset of sensor nodes. Alternatively, sensor nodes' transmission ranges can be limited as a function of their distance to the network border. Even under this policy a subset of the nodes become hotspots. On the other hand, nodes close the border cannot dissipate their energies completely because they cannot relay much data due the limits imposed on their transmission ranges. One possible solution to mitigate the uneven energy dissipation characteristic is to let the nodes that cannot dissipate their energies on communications reduce the amount of data they generate through computation so that the relay nodes convey less data. In this study we create a novel Linear Programming (LP) framework to model the energy cost of contextual privacy and multi-level data compression in WSNs.

“…In [13], two joint routing and scheduling algorithms which minimize the data delivery latency while enhancing the energy efficiency in WSNs are proposed and investigated through an MIP framework. In [14], the impact of limiting the number of incoming and outgoing links of nodes on the network lifetime is formulated as an MIP problem.…”

Section: Introductionmentioning

confidence: 99%

Optimal number of routing paths in multi-path routing to minimize energy consumption in wireless sensor networks

Incebacak

Biçakcı

et al. 2013

J Wireless Com Network

Self Cite

In wireless sensor networks, multi-path routing is proposed for energy balancing which prolongs the network lifetime as compared to single-path routing where utilization of a single route between a source node and the base station results in imbalanced energy dissipation. While it is evident that increasing the number of routing paths mitigates the problem of energy over-utilization in a subset of nodes acting as relays, the net effect of the proliferation of multiple routing paths on energy balancing remains unclear. It is imperative to keep the number of routing paths as low as possible without significantly deteriorating the network lifetime; therefore, determination of the optimal number of routing paths in multi-path routing by considering the tradeoff in routing complexity and network lifetime extension is an interesting research problem. In this study, to investigate the impact of the number of routing paths in multi-path routing on network-wide energy balancing under optimal operating conditions, we build a novel mixed integer programming framework. We explore the parameter space consisting of a number of paths, number of nodes, maximum transmission range, network area, and network topology. The results of the analysis show that by utilizing the optimization scheme proposed, it is possible to achieve near-optimal energy consumption (within 1.0% neighborhood of the case where no restrictions are imposed on the number of routing paths in multi-path routing) using at most two paths for each node.