Periphery deployment for wireless sensor systems with guaranteed coverage percentage

With the availability of tiny wireless sensors, it is now possible to track moving objects by placing such sensors on the targets, collecting needed data, and transmitting sensed data back to the sink for storage and analysis. For applications such as vessel clearance surveillance, landslide detection, conveyer monitoring, and body gesture tracking, the motions of the targets are often confined to a certain region, such as the water way or the mountain slope. To collect the data from the wireless sensors, base stations are usually needed, which are deployed at fixed positions around the monitored region. Unfortunately, due to issues such as potential interference, high packaging and deployment cost, and low reliability, many such applications could only deploy the base stations on the periphery of the monitored region. The question is how to deploy the base stations on the periphery so that they can cover the most area inside the monitored area. We formulate the periphery deployment problem and analyze the performance bound in terms of coverage percentage under both ideal and practical deployment conditions. Then, we describe a deployment procedure to solve the periphery deployment problem in polynomial time. The proposed algorithms are evaluated through extensive simulations drawn from a watercourse monitoring system. The results show that the proposed algorithms can reduce the size of the deployment set by 17% compared to the traditional area-coverage algorithms, and the coverage percentage is improved by 1.18 times.     

A survey on coverage and connectivity issues in wireless sensor networks

A wireless sensor network (WSN) is composed of a group of small power-constrained nodes with functions of sensing and communication, which can be scattered over a vast region for the purpose of detecting or monitoring some special events. The first challenge encountered in WSNs is how to cover a monitoring region perfectly. Coverage and connectivity are two of the most fundamental issues in WSNs, which have a great impact on the performance of WSNs. Optimized deployment strategy, sleep scheduling mechanism, and coverage radius cannot only reduce cost, but also extend the network lifetime. In this paper, we classify the coverage problem from different angles, describe the evaluation metrics of coverage control algorithms, analyze the relationship between coverage and connectivity, compare typical simulation tools, and discuss research challenges and existing problems in this area.     

无线传感器网络节点自调度冗余覆盖算法

对于能量受限的无线传感器网络,延长网络存活的时间很关键。针对这个问题,提出了一种基于能量均衡的传感器节点自调度冗余覆盖协议（SRCP）,通过仿真实验对该算法的有关性能进行了评价,性能评价表明：这种算法能有效使用节点能力,延长网络存活时间。     

一种无线多媒体传感器网络分区链路调度算法

链路干扰是无线多媒体传感器网络实现大容量、实时、可靠传输的主要困难。为提高多跳传输模式下无线网络性能,基于MAC层的调度算法得到了广泛关注。调度算法为每条链路分配合理的传输时槽,降低了冲突和重传次数,能显著提高网络传输性能。但随着网络规模的增大,无论是集中式还是分布式调度算法,都存在调度开销增大和性能降低的问题。针对这一问题,根据节点分布密度和承载网络流量大小,将网络划分为密集区域和稀疏区域。稀疏区域的节点传输冲突较小,直接采用CSMA的协议。密集区域的节点传输冲突大,采用基于队列长度的分布式调度。分区调度能够有效降低网络规模扩大导致的调度算法复杂性增大的问题。仿真实验表明,分区调度算法无论是在队列长度,还是在延时性能上,较传统算法有明显改善。     

A proportional fairness scheduling for wireless sensor networks

This paper describes a packet scheduling algorithm for wireless sensor networks (WSNs) that meets the proportional fairness principle. Based on the weighted round-robin strategy, the proposed scheduling algorithm allocates a different service quota to different traffic according to the average packet arrival rate. This guarantees proportional fairness in terms of the average packet delivery delay and the average packet loss ratio. Since the scheduling algorithm does not perform high-load operations such as time stamping and sorting, it can be implemented easily and is suitable for resource-limited WSNs. The proposed scheduling algorithm is tested in a WSN and is found to guarantee the proportional fairness of the average packet delivery delay when this is used as the performance metric, and to realize proportional fairness in the average packet loss ratio when all the queues are overflowing and the average packet loss ratio is used as the performance metric.     

Quantifying connectivity in wireless sensor networks with grid-based deployments

Measuring network connectivity under grid-based deployment in 3D space is a challenging problem in wireless sensor networks (WSNs). Solving such a problem becomes an even more intricate task with realistic deployment factors such as placement uncertainty and hindrances to wireless communication channels. While much work has been published on optimizing connectivity, only a few papers have addressed such realistic aspects which cause severe connectivity problems in practice. In this paper, we introduce a novel grid-based deployment metric, called Average Connectivity Percentage in order to characterize the deployed network connectivity when sensor placements are subject to random errors around their corresponding grid locations. A generic approach is proposed to assess and evaluate the proposed metric. This generic approach is independent of the grid-shape, random error distributions, and different environment-based channel characteristics. We apply the generic approach in two practical deployment scenarios: the grid-based deployment with bounded uniform errors and with unbounded normal errors. In both cases, the average connectivity percentage is computed numerically and verified via extensive simulations. Based on the numerical results, quantified effects of positioning errors and grid edge length on the average connectivity percentage are outlined.     

无线传感器网络中一种基于分簇的节点调度算法

本文研究m覆盖与连通的无线传感器网络中的节点调度问题,提出了一种两跳簇的概念,并在此基础上提出了一种新的节点调度算法.该算法可在不知道节点位置信息的情况下,将无线传感器网络中的所有节点较为均匀地指派到k(km)个不同的分组{0,1,...,k1}之中,且可同时保证每个分组中的节点具有全局连通性与较高的网络覆盖率.理论分析与实验结果表明,该算法具有比传统随机调度方法更好的节点调度性能,可更加有效地延长无线传感器网络的生命周期.     

Cluster based node scheduling method for wireless sensor networks

By researching on the node scheduling problem of m-covered and connected sensor networks,a new concept of two-hops-cluster is proposed in this paper,and based on it,a new distributed node scheduling algorithm THCNS for allocating all nodes in the sensor network into k(k≤m) different groups {0,1,...,k 1} is designed,without requiring location information.Our algorithm guarantees that each group to be connected and maintains the coverage ratio with high possibility.Theoretical analysis and simulation results show that it has better performance than previous randomized scheduling scheme,and can prolong the lifetime of the sensor network effectively.     

无线传感器网络中一种基于GEAR协议的节点调度策略

基于无线传感器网络地理能量感知路由(GEAR)协议,提出了一种面向查询式路由的节点调度策略GNSS.该策略针对GEAR协议中存在大量空闲节点和冗余节点的能耗问题,根据周期性路由信息,对节点进行角色分类,不同角色的节点执行不同的调度策略.通过节点调度节省了大量能量消耗,同时减少了数据传输量和通信碰撞带来的开销.仿真结果表明:与改进前的GEAR协议相比,该策略使网络生命周期提高了50%以上.     

A cross-layer transmission scheduling scheme for wireless sensor networks

In a wireless sensor network, the sensor nodes are densely deployed for detecting in many cases. One design challenge for such a network is how to devise a good data fusion algorithm for information retrieval. Noting that the channel state information (CSI) between the cluster head and the sensor nodes will influence the received bit energy noise ratio of the sensor nodes, we propose an optimal data fusion algorithm taking into account the CSI for a one-hop clustered wireless sensor network. On the basis of the fusion algorithm, we consider the redundancy of the sensor deployment and propose a cross-layer transmission scheduling scheme. By selecting proper set of sensor nodes to transmit their local information back in turn, the scheme can prolong the lifetime of the sensor network. The numerical and simulation results show that it can get a good tradeoff between the energy efficiency and the performance.     

无线传感器网络的连通性问题研究

无线传感器网络的初始配置最优可以减少传感器网络的拓扑变化和降低网络重置的能量消耗.对初始均匀随机分布的无线传感器网络的连通性进行了研究.运用覆盖理论给出了传感器节点的连通度概率分布模型,并在此模型基础上推导出传感器节点的通信半径与期望连通度概率最大之间的关系.仿真结果表明了结论的正确性.     

Connectivity and coverage maintenance in wireless sensor networks

One of the main design challenges for wireless sensor networks (WSNs) is to obtain long system lifetime without sacrificing system original performance such as communication connectivity and sensing coverage. A large number of sensor nodes are deployed in redundant fashion in dense sensor networks, which lead to higher energy consumption. We propose a distributed framework for energy efficient connectivity and coverage maintenance in WSNs. In our framework, each sensor makes self-scheduling to separately control the states of RF and sensing unit based on dynamic coordinated reconstruction mechanism. A novel energy-balanced distributed connected dominating set algorithm is presented to make connectivity maintenance; and also a distributed node sensing scheduling is brought forward to maintain the network coverage according to the surveillance requirements. We implemented our framework by C++ programming, and the simulation results show that our framework outperforms several related work by considerably improving the energy performance of sensor networks to effectively extend network lifetime.     

Energy-efficient scheduling for multiple access in wireless sensor networks: A job scheduling method

With the objective to minimize the transmission energy cost, we consider the energy-efficient scheduling problem in a single hop multi-access data gathering network. We first prove by theoretical induction that transmitting with reduced powers decreases the energy budget in a multi-access transmission. Given the optimal transmit powers, we then examine the multi-access capacity polymatroid and argue that the optimal rate control can be achieved by controlling the successive decoding order of the transmitting sensor nodes. Consequently, the multi-access scheduling problem is reformulated into the job scheduling problems and solved by adapting job scheduling policies. We also address the implementation issues and demonstrate via simulations that the proposed strategies are efficient in energy conservation.     

Multi-objective clustered-based routing with coverage control in wireless sensor networks

A wireless sensor network (WSN) generally consists of a large number of inexpensive power constrained sensors that are small in size and communicate over short distances to perform a predefined task. Realizing the full potential of WSN poses many design problems, especially those which involve tradeoffs between multiple conflicting optimization objectives such as coverage preservation and energy conservation. While both energy conservation routing protocols in a cluster-based WSNs and coverage-maintenance problems have been extensively studied in the literature, these two problems have not been integrated in a multi-objective optimization (MOO) manner. This paper employs a recently developed MOO algorithm, the so-called multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve simultaneously the energy conservation and coverage preservation design problems in cluster-based WSNs. The performance of the proposed approach, in terms of network lifetime and coverage is compared with the heuristic LEACH and SEP clustering protocols and with another prominent MOEA, the so-called non-dominated sorting genetic algorithm II (NSGA II). Simulation results reveal that MOEA/D provides a more efficient and reliable behavior over other approaches.     

能量有效的无线传感器网络动态任务调度算法

为减少无线传感器网络任务调度的能量消耗,平衡网络负载,提出能量最小化的动态任务调度算法。在感知动态环境的基础上,将传感器网络节点的覆盖率、可调度性等作为该问题的约束条件。将改进后的蚁群算法应用于任务调度算法中,通过迭代得到最优分配方案,引入信息熵提升剩余能量充沛的节点执行任务的几率。仿真结果表明,该算法在降低任务分配的执行时间、能量消耗量及优化网络负载平衡方面取得了较好的效果。