QoS Constrained Optimal Sink and Relay Placement in Planned Wireless Sensor Networks

We are given a set of sensors at given locations, a set of potential locations for placing base stations (BSs, or sinks), and another set of potential locations for placing wireless relay nodes. There is a cost for placing a BS and a cost for placing a relay. The problem we consider is to select a set of BS locations, a set of relay locations, and an association of sensor nodes with the selected BS locations, so that number of hops in the path from each sensor to its BS is bounded by hmax, and among all such feasible networks, the cost of the selected network is the minimum. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard, and is hard to even approximate within a constant factor. For this problem, we propose a polynomial time approximation algorithm (SmartSelect) based on a relay placement algorithm proposed in our earlier work, along with a modification of the greedy algorithm for weighted set cover. We have analyzed the worst case approximation guarantee for this algorithm. We have also proposed a polynomial time heuristic to improve upon the solution provided by SmartSelect. Our numerical results demonstrate that the algorithms provide good quality solutions using very little computation time in various randomly generated network scenarios

The Influence of Communication Range on Connectivity for Resilient Wireless Sensor Networks Using a Probabilistic Approach.

Wireless sensor networks (WSNs) consist of thousands of nodes that need to communicate with each other. However, it is possible that some nodes are isolated from other nodes due to limited communication range. This paper focuses on the influence of communication range on the probability that all nodes are connected under two conditions, respectively: (1) all nodes have the same communication range, and (2) communication range of each node is a random variable. In the former case, this work proves that, for 0menor queepsmenor quee^(-1) , if the probability of the network being connected is 0.36eps , by means of increasing communication range by constant C(eps) , the probability of network being connected is at least 1-eps. Explicit function C(eps) is given. It turns out that, once the network is connected, it also makes the WSNs resilient against nodes failure. In the latter case, this paper proposes that the network connection probability is modeled as Cox process. The change of network connection probability with respect to distribution parameters and resilience performance is presented. Finally, a method to decide the distribution parameters of node communication range in order to satisfy a given network connection probability is developed

The More Relay Nodes, the More Energy Efficient?

Abstract—Existing work has been focused on minimizing the number of relay nodes to maintain the connectivity of a sensor network. However, we believe replacing batteries for nodes or redeploying the network is either labor-intensive or impossible, so it is more desirable to reduce energy consumption even if we need to use slightly more nodes. The question we are trying to answer is: is it possible to greatly reduce energy consumption by increasing the number of relay nodes? To properly answer this question, we first designed an algorithm that finds the most energy efficient relay nodes placement for a given number of relay nodes. By observing the energy saving with different numbers of available relay nodes, we found that slightly increasing the number of relay nodes can significantly reduce energy consumption. On the contrary, blindly adding relay nodes does not necessarily improve energy efficiency when the number of relay nodes exceeds a certain threshold. Index Terms—wireless sensor networks, relay node placement, network deployment, energy efficiency I

A wireless sensor network-based approach to large-scale dimensional metrology

In many branches of industry, dimensional measurements have become an important part of the production cycle, in order to check product compliance with specifications. This task is not trivial especially when dealing with largescale dimensional measurements: the bigger the measurement dimensions are, the harder is to achieve high accuracies. Nowadays, the problem can be handled using many metrological systems, based on different technologies (e.g. optical, mechanical, electromagnetic). Each of these systems is more or less adequate, depending upon measuring conditions, user's experience and skill, or other factors such as time, cost, accuracy and portability. This article focuses on a new possible approach to large-scale dimensional metrology based on wireless sensor networks. Advantages and drawbacks of such approach are analysed and deeply discussed. Then, the article briefly presents a recent prototype system - the Mobile Spatial Coordinate-Measuring System (MScMS-II) - which has been developed at the Industrial Metrology and Quality Laboratory of DISPEA - Politecnico di Torino. The system seems to be suitable for performing dimensional measurements of large-size objects (sizes on the order of several meters). Owing to its distributed nature, the system - based on a wireless network of optical devices - is portable, fully scalable with respect to dimensions and shapes and easily adaptable to different working environments. Preliminary results of experimental tests, aimed at evaluating system performance as well as research perspectives for further improvements, are discusse

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power

A Framework for the Capacity Evaluation of Multihop Wireless Networks

Accepted for publications : march 19th 2009. OPTx-editorial-board=yes, OPTx-proceedings=yes, OPTx-international-audience=yesInternational audienceThe specific challenges of multihop wireles networks lead to a strong research effort on efficient protocols design where the offered capacity is a key objective. More specifically, routing strategy largely impacts the network capacity, i.e. the throughput offered to each flow. In this work, we propose a complete framework to compute the upper and the lower bounds of the network capacity according to a physical topology and a given routing protocol. The radio resource sharing principles of CSMA-CA is modeled as a set of linear constraints with two models of fairness. The first one assumes that nodes have a fair access to the channel, while the second one assumes that on the radio links. We then develop a pessimistic and an optimistic scenarios for radio resource sharing, yielding a lower bound and an upper bound on the network capacity for each fairness case. Our approach is independent of the network topology and the routing protocols, and provides therefore a relevant framework for their comparison. We apply our models to a comparative analysis of a well-known flat routing protocol OLSR against two main self-organized structure approaches, VSR and localized CDS