Small-scale Sensor Networks Research Articles

Radio environment maps for military cognitive networks: density of small-scale sensor network vs. map quality

In this paper, we present the dependency between density of a sensor network and map quality in the radio environment map (REM) concept. The architecture of REM supporting military communications systems is described. The map construction techniques based on spatial statistics and transmitter location determination are presented. The problem of REM quality and relevant metrics are discussed. The results of field tests for UHF range with a different number of sensors are shown. Exemplary REM maps with different interpolation algorithms are presented. Finally, the problem of density of a sensor network versus REM map quality is analyzed.

Improved Routing in Wireless Sensor Networks Using Harmony Search Algorithm

One of the most important issues of wireless sensor networks is how to transfer information from the network nodes to a base station and choose the best possible path for this purpose. Choosing the best path can be based on different factors such as energy consumption, response time, delay, and data transfer accuracy. Increasing the network lifetime is the most challenging problem. One of the latest energy-aware routing methods is to use the harmony search algorithm in the small-scale sensor networks. The aim of this study is to introduce the harmony search algorithm as a successful metaheuristic algorithm for wireless sensor network routing in order to increase the lifetime of such networks. This study is intended to improve the objective function for energy efficiency in the harmony search algorithm to establish balance between the network energy consumption and path length control. Therefore, it is necessary to choose the initial energy of each node randomly from a certain range as the path energy consumption should be low to choose a path which can consider the residual energy. In other words, a path should be chosen to establish balance between the network energy consumption and the minimum residual energy. The simulation results indicate that the proposed objective function provides a longer lifetime by 26.12% compared with EEHSBR.

Barrier coverage in wireless sensor networks with adjustable sensing ranges

In this paper, we study the barrier lifetime maximisation (BLM) and barrier gap mending (BGM) problem in a sensor network, where sensors can choose to use different sensing ranges when constructing a sensor barrier. In the BLM problem, for small–scale sensor networks, we propose a linear programming optimisation method. For large–scale sensor networks, we propose two distributed heuristics to select a next node to construct barriers. Simulation results show that compared with the randomised one, the greedy scheme can achieve longer lifetime. In the BGM problem, we study how to efficiently mend barrier gaps in a hybrid sensor network consisting of both stationary and mobile sensors. We propose two gap mending schemes: the min–max scheme to minimise the maximal energy consumption to move sensors, and the max–lifetime scheme to maximise the lifetime of barrier coverage after mending all gaps. Simulation results show that the min–max scheme can achieve a lower maximal moving distance and the max–lifetime scheme can efficiently extend the barrier lifetime.

Cross Layer Optimization for Lifetime Maximization in Wireless Sensor Network Based on Particle Swarm Optimization

Network lifetime is a critical metric in the design of energy-constrained wireless sensor networks. In this paper, we consider the joint cross layer optimization of the physical layer, medium access control layer and routing layer to maximize network lifetime of a multi-sources and single-sink wireless sensor network with energy constraints. We focus on synchronous small-scale sensor network with interference-free link scheduling and practical MPSK link transmission scheme. As the network lifetime maximization problem is a constrained non-convex optimization problem that is difficult to be solved, and the particle swarm optimization algorithm is a good intelligent algorithm, we employ it to solve the problem mentioned above effectively in this paper. The penalty function technique is brought in to work out the constrained optimization problem by converting it to an unconstrained optimization problem. Simulation results show the effectiveness of the proposed algorithm in energy saving and network lifetime maximization, and the particle swarm optimization can solve the network lifetime maximization problem fast and efficiently.

Analyzing localization errors in one-dimensional sensor networks

One-dimensional sensor networks can be found in many fields and demand node location information for various applications. Developing localization algorithms in one-dimensional sensor networks is trivial, due to the fact that existing localization algorithms developed for two- and three-dimensional sensor networks are applicable; nevertheless, analyzing the corresponding localization errors is non-trivial at all, because it is helpful to improving localization accuracy and designing sensor network applications. This paper deals with localization errors in distance-based multi-hop localization procedures of one-dimensional sensor networks through the Cramér–Rao lower bound (CRLB). We analyze the fundamental behaviors of localization errors and show that the localization error for a sensor is locally determined by network elements within a certain range of this sensor. Moreover, we break down the analysis of localization errors in a large-scale sensor network into the analysis in small-scale sensor networks, termed unit networks, in which tight upper and lower bounds on the CRLB can be established. Finally, we investigate two practical issues: the applicability of the analysis based on the CRLB and the optimal anchor placement.

Evaluation of a Heterogeneous Sensor Network Architecture for Highly Mobile Users

This paper presents experimental results of a heterogeneous sensor network architecture, which is a combination of a wireless sensor network and a personal area network. The proposed architecture uses the IEEE 802.15.4 standard to transmit sensor data to a sensor node which in turn forwards the data using TCP/IP to a database on the Internet via a Bluetooth-equipped mobile phone and the mobile telephone access network. The performance of the entire communication chain is evaluated. First, a 3G network's performance is evaluated by measuring its round trip time for packet transmission. Second, the real-world end-to-end delay between a sensor node and a database server on the Internet is measured using two different experimental set-ups: single-hop transmission and two hops transmission. Finally, the proposed architecture's scalability is estimated in a Matlab simulation using the results of the experiments as a base. The results show that the proposed architecture is applicable for small-scale sensor networks used by highly mobile users.

Wireless Sensor Networks for Oceanographic Monitoring: A Systematic Review

Monitoring of the marine environment has come to be a field of scientific interest in the last ten years. The instruments used in this work have ranged from small-scale sensor networks to complex observation systems. Among small-scale networks, Wireless Sensor Networks (WSNs) are a highly attractive solution in that they are easy to deploy, operate and dismantle and are relatively inexpensive. The aim of this paper is to identify, appraise, select and synthesize all high quality research evidence relevant to the use of WSNs in oceanographic monitoring. The literature is systematically reviewed to offer an overview of the present state of this field of study and identify the principal resources that have been used to implement networks of this kind. Finally, this article details the challenges and difficulties that have to be overcome if these networks are to be successfully deployed.

Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks

The general joint design of the physical, MAC, and routing layers to minimize network energy consumption is complex and hard to solve. Heuristics to compute approximate solutions and high-complexity algorithms to compute exact solutions have been previously proposed. In this paper, we focus on synchronous small-scale networks with interference-free link scheduling and practical MQAM link transmission schemes. We show that the cross-layer optimization problems can be closely approximated by convex optimization problems that can be efficiently solved. There are two main contributions of this paper. First of all, we minimize the total network energy that includes both transmission and circuit energy consumptions, where we explore the tradeoff between the two energy elements. Specifically, we use interference-free TDMA as the medium access control scheme. We optimize the routing flow, TDMA slot assignment, and MQAM modulation rate and power on each link. The results demonstrate that the minimum energy transmission scheme is a combination of multihop and single-hop transmissions for general networks; including circuit energy favors transmission schemes with fewer hops. Secondly, based on the solved optimal transmission scheme, we quantify the best trade-off curve between delay and energy consumption, where we derive a scheduling algorithm to minimize the worst-case packet delay.