Network Lifetime Maximization for Estimation in Multihop Wireless Sensor Networks

We consider the distributed estimation by a network consisting of a fusion center and a set of sensor nodes, where the goal is to maximize the network lifetime, defined as the estimation task cycles accomplished before the network becomes nonfunctional. In energy-limited wireless sensor networks, both local quantization and multihop transmission are essential to save transmission energy and thus prolong the network lifetime. The network lifetime optimization problem includes three components: i) optimizing source coding at each sensor node, ii) optimizing source throughput of each sensor node, and iii) optimizing multihop routing path. Fortunately, source coding optimization can be decoupled from source throughput and multihop routing path optimization, and is solved by introducing a concept of equivalent 1-bit MSE function. Based on the optimal source coding, the source throughput and multihop routing path optimization is formulated as a linear programming (LP) problem, which suggests a new notion of character-based routing. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.     

Energy Optimization in Multihop Wireless Embedded and Sensor Networks

This paper provides an analytical model for the study of energy consumption in multihop wireless embedded and sensor networks where nodes are extremely power constrained. Low-power optimization techniques developed for conventional ad hoc networks are not sufficient as they do not properly address particular features of embedded and sensor networks. It is not enough to reduce overall energy consumption, it is also important to maximize the lifetime of the entire network, that is, maintain full network connectivity for as long as possible. This paper considers different multihop scenarios to compute the energy per bit, efficiency and energy consumed by individual nodes and the network as a whole. The analysis uses a detailed model for the energy consumed by the radio at each node. Multihop topologies with equidistant and optimal node spacing are studied. Numerical computations illustrate the effects of packet routing, and explore the effects of coding and medium access control. These results show that always using a simple multihop message relay strategy is not always the best procedure.     

Trade-Off Analysis of Energy Consumption and Image Quality for Multihop Wireless Sensor Networks

It has become necessary in recent years to observe and monitor some physical phenomena. This was made possible by the emergence of wireless sensor networks. The main characteristic of such networks is nodes with scarce resources. Given the stringent resource constraints, nodes are limited in energy, memory and computational power. These resource constraints pose serious difficulties for image processing and transmission to the destination. Therefore, image transfer in wireless sensor networks presents major challenge which raises issues related to its representation, its storage and its transmission. Based on wavelet transform an Adaptive Energy Efficient Wavelet Image Compression Algorithm is proposed in order to be suitable for wireless sensor network. In addition, an identification of the wavelet image compression parameters is investigated to analyze the trade-offs between the energy saving, and the image quality. Performance studies indicate that the proposed scheme enabling significant reductions in computation as well as communication energy needed, with minimal degradation in image quality.     

Cross-Layer Collaborative In-Network Processing in Multihop Wireless Sensor Networks

Emerging wireless sensor network (WSN) applications demand considerable computation capacity for in-network processing. To achieve the required processing capacity, cross-layer collaborative in-network processing among sensors emerges as a promising solution: sensors do not only process information at the application layer, but also synchronize their communication activities to exchange partially processed data for parallel processing. However, scheduling computation and communication events is a challenging problem in WSNs due to limited resource availability and shared communication medium. In this work, an application-independent task mapping and scheduling solution in multihop homogeneous WSNs, multihop task mapping and scheduling (MTMS), is presented that provides real-time guarantees. Using our proposed application model, the multihop channel model, and the communication scheduling algorithm, computation tasks and associated communication events are scheduled simultaneously. The dynamic voltage scaling (DVS) algorithm is presented to further optimize energy consumption. Simulation results show significant performance improvements compared with existing mechanisms in terms of minimizing energy consumption subject to delay constraints     

Proportional Fair Scheduling with Capacity Estimation for Wireless Multihop Networks

In this paper, we investigate the scheduling problem to achieve the proportional fairness among the flows in wireless multihop networks with time-varying channel capacity. Using the signal to interference noise ratio and the outage probability, we present an estimate of time-varying capacity. Then, we achieve the proportional fairness in terms of maximizing the network utility function with consideration of fast fading without measurement of channel state information. Finally, we show that the proposed scheme results in better performance compared to the existing schemes through the simulation results.     

Blind Adaptive Weighted Aggregation Scheme for Event Detection in Multihop Wireless Sensor Networks

The problem of decision fusion for event detection in Wireless Sensor Networks is the prime focus of this paper. Our proposed algorithm focuses on single hop (star) and multihop (tree) topologies, which are commonly deployed wireless sensor network topologies. In order to minimize the overall energy consumption in the network, a transmission constraint of one-bit is imposed on each sensor node. This poses a challenging problem of designing a one-bit decision fusion rule at every fusion center, which improves the overall detection accuracy at the sink node. The absence of apriori knowledge of each sensor’s local performance indices, makes the existing optimum fusion rule infeasible. Moreover, in the absence of a training sequence of true event occurrences, existing Adaptive distributed detection techniques also become inapplicable. In this setup, the key contribution of this paper is a Least Mean Squares based Blind Adaptive Weighted Aggregation Scheme (Blind-AdWAS) for Wireless Sensor Networks with tree topology. We extend our earlier work (Jagyasi et al. in Proceedings of 11th international symposium on wireless personal multimedia communication, 2008) to include an analysis of the effect of Rayleigh flat fading channel on Blind-AdWAS in comparison with existing channel-aware optimum and sub- optimum aggregation schemes. Even in the absence of any channel knowledge or knowledge of performance indices, Blind-AdWAS demonstrates robustness in event detection performance.     

Performance Evaluation of Dynamic Zone Radius Estimation in ZRP for Multihop Adhoc Networks

Wireless Personal Communications - Due to self-organizing and self-configuring nature of multihop adhoc networks, routing is the most challenging task. Zone routing protocol (ZRP) is one of the...     

Asymptotically Optimal Energy-Aware Routing for Multihop Wireless Networks With Renewable Energy Sources

In this paper, we develop a model to characterize the performance of multihop radio networks in the presence of energy constraints and design routing algorithms to optimally utilize the available energy. The energy model allows us to consider different types of energy sources in heterogeneous environments. The proposed algorithm is shown to achieve a competitive ratio (i.e., the ratio of the performance of any offline algorithm that has knowledge of all past and future packet arrivals to the performance of our online algorithm) that is asymptotically optimal with respect to the number of nodes in the network. The algorithm assumes no statistical information on packet arrivals and can easily be incorporated into existing routing schemes (e.g., proactive or on-demand methodologies) in a distributed fashion. Simulation results confirm that the algorithm performs very well in terms of maximizing the throughput of an energy-constrained network. Further, a new threshold-based scheme is proposed to reduce the routing overhead while incurring only minimum performance degradation.     

Wireless Sensor Networks Localization Using Progressive Isomap

Wireless Personal Communications - This paper proposes a progressive Isomap algorithm for node localization. The algorithm is an extension of centralized Isomap and is capable of effectively...     

Spatial Energy Balancing Through Proactive Multipath Routing in Wireless Multihop Networks

In this paper, we investigate the use of proactive multipath routing to achieve energy-efficient operation of ad hoc wireless networks. The focus is on optimizing tradeoffs between the energy cost of spreading traffic and the improved spatial balance of energy burdens. We propose a simple scheme for multipath routing based on spatial relationships among nodes. Then, combining stochastic geometric and queueing models, we develop a continuum model for such networks, permitting an evaluation of different types of scenarios, i.e., with and without energy replenishing and storage capabilities. We propose a parameterized family of energy balancing strategies and study the spatial distributions of energy burdens based on their associated second-order statistics. Our analysis and simulations show the fundamental importance of the tradeoff explored in this paper, and how its optimization depends on the relative values of the energy reserves/storage, replenishing rates, and network load characteristics. For example, one of our results shows that the degree of spreading should roughly scale as the square root of the bits middot meters load offered by a session. Simulation results confirm that proactive multipath routing decreases the probability of energy depletion by orders of magnitude versus that of a shortest path routing scheme when the initial energy reserve is high     

基于HARQ协议的多跳中继网络能量效率的跨层优化设计

该文针对瑞利衰落信道中采用Chase合并混合自动重传请求(CC-HARQ)协议的多跳中继网络提出一种基于跨层设计的能量效率优化策略。为实现能量效率的最大化,基于对数域线性阈值的平均误帧率模型,推导出多跳CC-HARQ系统能量效率的闭合表达式,进而设计了最优发送帧长策略和最优发送功率分配方案,其次,针对发送帧长和发送功率分析了两者的联合优化方案。仿真结果验证了理论分析的正确性和可行性,仿真对比实验表明所提跨层优化设计方案可以有效提升实际多跳网络的能量效率性能。     

A Likelihood-Based Multiple Access for Estimation in Sensor Networks

In a wireless sensor network (WSN), the nodes collect independent observations about a nonrandom parameter thetas to be estimated, and deliver informations to a fusion center (FC) by transmitting suitable waveforms through a common multiple access channel (MAC). The FC implements some appropriate fusion rule and outputs the final estimate of thetas. In this paper, we introduce a new access/estimation scheme, here referred to as likelihood-based multiple access (LBMA), and prove it to be asymptotically efficient in the limit of increasingly large number of sensors , when the used bandwidth is allowed to scale as W ~cap^alpha,O.5 < alpha < 1 . The proposed approach is easy to implement, and simply relies upon the very basic property that the log likelihood is additive for independent observations, and upon the fact that the (noiseless) output of the MAC is just the sum of its inputs. Thus, the optimal fusion rule is automatically implemented by the MAC itself.     

Distributed Estimation in Energy-Constrained Wireless Sensor Networks

In this paper, we consider distributed estimation of a noise-corrupted deterministic parameter in energy-constrained wireless sensor networks from energy-distortion perspective. Given a total energy budget allowable to be used by all sensors, there exists a tradeoff between the subset of active sensors and the energy used by each active sensor in order to minimize the estimation MSE. To determine the optimal quantization bit rate and transmission energy of each sensor, a concept of equivalent unit-energy MSE function is introduced. Based on this concept, an optimal energy-constrained distributed estimation algorithm for homogeneous sensor networks and a quasi-optimal energy-constrained distributed estimation algorithm for heterogeneous sensor networks are proposed. Moreover, the theoretical energy-distortion performance bound for distributed estimation is addressed and it is shown that the proposed algorithm is quasi-optimal within a factor 2 of the theoretical lower bound. Simulation results also show that the proposed method can achieve a significant reduction in the estimation MSE when compared with other uniform schemes. Finally, the proposed algorithm is easy to implement in a distributed manner and it adapts well to the dynamic sensor environments.     

无线传感器网络节能策略分析

无线传感器网络作为当今广泛使用的一项技术,其生存周期一般都很长,但节点多采用电池供电,能量有限。而网络的节点的数目太多,如要更换电池工作量太大无法实现。因此,在正常运行和保证系统功能的条件下,尽量减少能耗的节能技术,是本文所研究的问题。     

A Multiaccess Protocol for Multihop Radio Networks

We describe an adaptive multiaccess channel protocol for use in radio networks with an arbitrary distribution of stationary hidden nodes, which provides the nodes with controlled, collision-free access to the channel. The protocol can be considered to belong to the BRAM [5] protocol family, but differs in significant ways from BRAM. In this paper we describe the tenets of the protocol, then develop the protocol, and finally develop analytic expressions for its expected throughput and delay performance. Given these delay-throughput expressions, we show how protocol "delay" optimization can be achieved by dynamic adjustment of a protocol parameter as the network traffic load changes.     

无线传感器网络能量均衡路由算法

设计了一种能量均衡的路由算法.路由的建立分两个阶段,在簇头建立阶段,让候选节点在覆盖范围内以剩余能量的多少和所处位置为标准来竞选簇头,以使簇头分布均匀,平衡网络覆盖;在通信阶段,根据簇头节点的剩余能量大小和其距离基站的远近,采用多跳的簇间通信方式建立路由,以此来降低簇头节点的通信负载.仿真结果表明该算法能够有效降低网络能耗和延长网络生存时间.     

能量收集认知多跳中继网络中断性能分析及优化

针对能量收集认知无线网络中的多跳中继传输问题,该文构建了一种新的具有主网络干扰的功率信标(PB)辅助能量收集认知多跳中继网络模型,并提出单向传输方案.在干扰链路统计信道状态信息场景下,推导了次网络精确和渐近总中断概率闭合式.针对精确总中断概率表达式的复杂性和非凸性,采用自适应混沌粒子群优化(ACPSO)算法对次网络总中断性能进行优化.仿真结果表明,PB功率、干扰约束、次网络跳数、能量收集比率、主接收端数目和信道容量阈值等参数对中断性能影响显著,所提算法能快速和有效地对网络中断性能进行优化.     

Implementation Issues for OFDM-Based Multihop Cellular Networks

In this article we present various issues that need careful design for the successful implementation of OFDMA-based multihop cellular networks which need incorporation of relay terminals. The first issue we present is synchronization. We show that it is not a problematic issue for infrastructure-based relaying, where the relay is deployed by a system operator at strategic points in the cell. Second, we focus on the advantage of adaptive relaying and provide a frame structure to enable adaptive relaying in a cellular network operating according to the IEEE 802.16e standard. The third issue we present is related to hardware implementation aspects. Hardware performance and resource usage analysis will show that cooperative diversity schemes increase hardware resource usage and power/energy consumption at mobile terminals. The last issue we present is within the context of link layer ARQ, where we propose a novel retransmission method, named local retransmission-ARQ (LR-ARQ), which is designed to take advantage of the multihop nature of the cellular network. Practically, we show that LR-ARQ improves performance with respect to its single-hop counterpart in terms of cell latency, goodput, and throughput.     

Energy-Efficient SINR-Based Routing for Multihop Wireless Networks

In this paper, we develop an energy-efficient routing scheme that takes into account the interference created by existing flows in the network. The routing scheme chooses a route such that the network expends the minimum energy satisfying with the minimum constraints of flows. Unlike previous works, we explicitly study the impact of routing a new flow on the energy consumption of the network. Under certain assumptions on how links are scheduled, we can show that our proposed algorithm is asymptotically (in time) optimal in terms of minimizing the average energy consumption. We also develop a distributed version of the algorithm. Our algorithm automatically detours around a congested area in the network, which helps mitigate network congestion and improve overall network performance. Using simulations, we show that the routes chosen by our algorithm (centralized and distributed) are more energy efficient than the state of the art.