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With the promise of being a revolutionary innovation for ubiquitous surveillance and monitoring, wireless sensor networks have attracted increasing interest from both academia and industry. One of the critical challenges facing successful WSN implementation is limited lifetime, which is imposed by the limited power supply of non-replenishable batteries on devices. In this article we concentrate on the impact of device provisioning on the usable system lifetime. We introduce a device provisioning framework based on hierarchical communication architecture. The device provisioning strategies are classified into two groups based on the application scenarios: deterministic and random. We investigate and compare the latest approaches for deterministic and random device provisioning. We also discuss open issues in each category.

Due to cost constraints and limited sensing capability of sensor nodes, it may be impossible or unrealistic for a wireless sensor network to provide full area coverage in some circumstances. In this paper, we introduce the novel concept of information-oriented sensing coverage, which measures the actual information utility obtained by a wireless sensor network. An information-oriented sensor deployment algorithm is proposed. The algorithm makes use of the fact that in many applications the importance or the information utility at different locations is non-uniform across the sensing field. The effectiveness of the proposed algorithm is studied using simulation. Being a pioneering effort in this area, our work paves a new direction of sensor deployment.

Due to the cost constraint, it is impossible or unnecessary for a wireless sensor network to provide full area coverage in many applications. To mitigate the negative impacts of incomplete coverage, it is critical to realize that the importance of different locations of a sensing field is often non-uniform in practice. By strategically allocating more sensor nodes to the area of more importance, the differential random deployment can effectively decrease the loss for not detecting interesting events, as compared to the uniform random deployment. In this paper, we study the differential random deployment of sensor nodes in depth. We discuss a number of factors that affect the design of the differential random deployment density function. Because of the inherent complexity, we propose a heuristic structure of the differential deployment density function. The effectiveness of our proposal is verified in the performance study via simulation.

Device deployment is a fundamental issue of WSN provisioning. The types, number, and locations of devices determine many intrinsic properties of a WSN, such as coverage, connectivity, cost and lifetime. In this paper, we explore the problem of the optimal WSN deployment, with an objective of minimizing the network cost with lifetime constraint. We discuss and identify the characteristics of a type of WSN applications. The ultimate objectives of the device deployment for such applications are presented and discussed. We refine a deployment problem in a practical and fundamental scenario. We model this problem with the minimum set covering problem. Based on a recursive algorithm, a deterministic deployment strategy is proposed.

Grid-based sensor deployment is an effective and efficient practice for provisioning wireless sensor networks. Previous work has addressed grid-based deployment of sensors in order to guarantee sensing coverage under the assumption that each device can be placed exactly at the grid vertices. However, in reality, the accuracy of device placement may be subject to various errors, which are shown to impair the sensing coverage. To overcome the negative impacts of these errors, the grid resolution and the number of devices to be deployed should be re-evaluated. In this paper, two deployment errors are identified, namely, misalignment and random errors. We derive the minimum number of sensors required by a robust grid-based sensor deployment assuming that the errors are bounded. This research shows that when designing a realistic large-scale grid-based sensor deployment, errors in device placement must be taken into account.

While a lot of existing research attempts to extend the lifetime of a wireless sensor network (WSN) by designing energy efficient networking protocols, the impact of random device deployment on system lifetime is not stressed enough. Some research efforts have tried to optimize device deployment with respect to lifetime by assuming devices can be placed deliberately. However, the methodologies and solutions therein are not applicable to a randomly deployed large scale WSN. In this research, we propose three random deployment strategies for relay nodes in a heterogeneous WSN, namely, connectivity- oriented, lifetime-oriented and hybrid deployment. We investigate how a strategy can affect both connectivity and network lifetime of a multi-hop heterogeneous WSN, in which relay nodes transmit data to the base station via multi-hop relay. The performance of the three strategies is evaluated through simulations. The results of this research provide a viable solution to the problem of optimizing provisioning of a large scale heterogeneous WSN.

In this paper, we propose a novel single hop-clustering scheme called step wise adaptive clustering hierarchy (SWATCH). SWATCH relieves the CH number variability problem by employing stepwise CH selection in two stages. It is a dynamic and straightforward scheme as LEACH. However, instead of selecting all CHs in one step, SWATCH splits the selection phase into an initial selection stage and an add-on selection stage. The initial selection is similar to LEACH. However, if the number of CHs in the initial selection is below a pre-determined target, the add-on selection will be invoked and will continue until an acceptable number of CHs have been selected. As a result, the number of CHs selected in each round tends to congregate in a narrow range around the optimal value. In order to evaluate the performance of SWATCH, we develop a hierarchical Markov chain model to track the behavior of the system. Numerical results verify our design objective in that the number of selected CHs highly conforms to the optimal value. Based on the results, an optimal number of CHs are greatly reduced the communication energy.

In this paper, the problem of relay node placement in heterogeneous wireless sensor networks (WSNs) is addressed. As all nodes are energy limited, placement strategies aimed at minimizing network cost with constraints on lifetime and connectivity are presented. Based on a two-phase placement framework, a heuristic algorithm to place the second phase relay nodes (SPRNs) is proposed. Furthermore, a lower bound of the optimal solution is derived. The efficacy of our proposal is investigated in both grid networks and random networks. The work of this paper provides guidance for implementing feasible WSNs for civilian applications

Device deployment is a major challenge to successful implementation of large scale wireless sensor network (WSN) applications. The number and positions of devices determine many intrinsic properties of a WSN system. However, the deployment issue has mostly been confined to studies concerning coverage and connectivity. The impact of device deployment on the usability or system lifetime has been largely neglected. In this research, we investigate how a deployment strategy can affect both connectivity and network lifetime of a WSN. Based on quantitative analysis of such effects, we propose three deployment strategies, namely, connectivity-oriented, lifetime-oriented, and hybrid deployment. The performance of the three strategies is evaluated through simulation. The results of this research provide tangible guidance of efficient provisioning for large scale WSNs.