One of the fundamental design challenges in designing a Wireless Sensor Network (WSN) is to maximize the network lifetime, as each sensor node of the network is equipped with a limited power battery. To overcome this challenge, different methods were developed in the last few years using such techniques as network protocols, data fusion algorithms using low power, energy efficient routing, and locating optimal sink position. This paper focuses on finding the optimal sink position. Relay nodes are introduced in conjunction with the sensor nodes to mitigate network geometric deficiencies since in most other approaches the sensor nodes close to the sink become heavily involved in data forwarding and, thus, their batteries are quickly depleted. A Particle Swarm Optimization (PSO) based algorithm is used to locate the optimal sink position with respect to those relay nodes to make the network more energy efficient. The relay nodes communicate with the sink instead of the sensor nodes. Tests show that this approach can save at least 40% of the energy and prolong the network lifetime.

This paper describes an optimal power allocation scheme for orthogonal frequency division multiple access two-way relay networks with physical network coding. The aim is to enhance the achievable sum rate of the terminals for a constrained total transmit power. Convex optimization is used to derive a closed-form solution for the power allocation between the relay node and the two terminals. This reduces the variable dimensionality of the objective function for the power assignment problem among multiple carriers when the total transmit power is constrained. This solution is then used to derive the optimal power control scheme. This method reduces the implementation complexity compared with the traditional resource allocation scheme. Numerical and simulation results show that the approach achieves almost the optimal sum rate and outperforms the fixed power assignment method with less computational load in various scenarios.

Current highway tunnel lighting control systems are often manually controlled, resulting in significant energy waste. This article designs a fuzzy control algorithm for tunnel lighting energy control systems. The system uses LED (Light Emitting Diode) lighting, so the fuzzy control algorithm is designed for LED lights. The traffic and the natural illumination level are used as parameters in the intelligent lighting control algorithm. This system has been deployed in the Lengshui tunnel on the 49th provincial highway of Zhejiang province and operated for more than six months. The performance results show that the energy conservation system provides sufficient lighting levels for traffic safety with significant energy conservation.

Most current Global System for Mobile Communications (GSM) frequency planning methods evaluate the interference and assign frequencies based on measurement reports. Assigning the same or adjacent frequencies to cells close to each other will introduce co-channel and adjacent channel interference which will reduce network performance. Traditionally, man power is used to check and allocate new frequencies which is time consuming and the accuracy is not satisfactory. This paper presents an intelligent analysis method for optimization of co-channel and adjacent channel interference by exploiting cell configuration information. The method defines an interference evaluation model by analyzing various factors such as the base station layer, the azimuth ward relationship, and the cell neighborhood relationships. The interference for each frequency is evaluated and the problem frequencies are optimized. This method is verified by a large number of actual datasets from an in-service GSM network. The results show this method has better intelligence, accuracy, timeliness, and visualization than traditional methods.

A large proportion of Internet of Things (IoT) applications are internally publish/subscribe in nature, and traditional architecture cannot support them efficiently and flexibly. In essence, supporting efficient publish/subscribe systems requires data-oriented naming and efficient multicast. Since deployment of native IP-based multicast has failed, overlay-based multicast has become the practical choice. Since load balancing between heterogeneous nodes is an important issue, designing an optimal load balancing overlay network for publish/subscribe systems is a necessary endeavor. This study focuses on the optimal load balancing overlay design problem for topic-based publish/subscribe systems in a heterogeneous environment (in terms of node processing power, bandwidth, and reachability). The Minimum Idle Degree (MID) model is introduced to capture the heterogeneity of overlay nodes. Based on the MID model, new node load measures are defined that can accommodate heterogeneous server capacities and capture the node load in publish/subscribe systems more accurately than traditional measures. A new optimization problem, Maximum Minimum Idle Degree Topic-Connected Overlay (MMID-TCO), is established. This problem is NP-complete and a constant approximation algorithm does not exist for this problem (unless P = NP). Based on MID metrics, the Maximum Minimum Idle Degree Overlay Design Algorithm (MMID-ODA), which has polynomial time, is introduced. To improve performance, an approach that breaks down the problem into several small-scale problems by exploiting the potential inherent disjoint characteristic in the subscription table is presented. Simulation results show that the proposed algorithm is able to achieve better load balance than MinMax-ODA in a heterogeneous environment.

The powerful processors and the variety of sensors in new and upcoming mobile Internet devices, such as iPhones and Android-based smart phones, can be leveraged to build cyber-physical applications that collect sensor data from the real world and communicate it back to the Internet for comprehensive processing. Available bandwidth measurement has been discussed previously in the computer networking community. Currently, it is important for cyber-physical applications to behave smartly since these applications prefer small data packets, short round-trip times, and sudden bursts of traffic. A new available bandwidth measurement technique for cyber-physical applications, SOProbe, was introduced and its accuracy was verified through ns-2 simulation. The experimental data indicate that this methodology can enable the gateway node to measure the available bandwidth of a path at low cost.

In recent years, underwater acoustic wireless sensor networks have been used in many areas. There have been many field trials of acoustic propagation models and statistics for shallow water conditions. However, field trials are limited environmentally and, hence, not widely accepted. Simulations of the impulse response of a shallow underwater acoustic channel allows less expensive system tests that are reproducable. This paper presents a shallow water acoustic channel model based on the actual acoustic propagation characteristics with path attenuation, ambient noise, multiple paths, and Doppler effects. The second-order statistical characteristics of the simulation model are verified with the autocorrelations and crosscorrelations of the quadrature components and the complex envelopes of channel impulse responses. The channel model is implemented in Matlab with the results showing that the absorption coefficient and path losses are both dependent on the frequencies and propagation distances and that the path gain can be improved with Light of Sight (LOS) and short range acoustic propagation. Analysis of the channel impulse response and the frequency response that the zero-order Bessel function of first kind can be used to describe the correlation functions for the impulse response. The shallow underwater acoustic channel is time-varying and can not be modeled as a wide-sense stationary-uncorrelated scattering channel.

The coverability of Wireless Sensor Networks (WSNs) is essentially a Quality of Service (QoS) problem that measures how well the monitored area is covered by one or more sensor nodes. The coverability of WSNs was examined by combining existing computational geometry techniques such as the Voronoi diagram and Delaunay triangulation with graph theoretical algorithmic techniques. Three new evaluation algorithms, known as CRM (Comprehensive Risk Minimization), TWS (Threshold Weight Shortest path), and CSM (Comprehensive Support Maximization), were introduced to better measure the coverability. The experimental results show that the CRM and CSM algorithms perform better than the MAM (MAximize Minimum weight) and MIM (MInimize Maximum weight) algorithms, respectively. In addition, the TWS algorithm can provide a lower bound detection possibility that accurately reflects the coverability of the wireless sensor nodes. Both theoretical and experimental analyses show that the proposed CRM, TWS, and CSM algorithms have O(n²) complexity.

The Clapping and Broadcasting Synchronization (CBS) algorithm, which is specifically designed for large-scale sensor networks with low communication overhead and high synchronization accuracy, is introduced. The CBS protocol uses broadcasting rather than pairwise communication to accomplish synchronization. In the CBS scheme, the initial offset of local clocks can be successfully eliminated by the operation of clapping nodes, which leads to significant improvement in synchronization accuracy. The CBS protocol was implemented on the TelosB platform and its performance was evaluated in a variety of experiments. The results demonstrate that the CBS protocol outperforms the current state-of-the-art approach, the Flooding Time Synchronization Protocol (FTSP), in both single-hop and multi-hop scenarios in terms of synchronous precision and energy consumption. In multi-hop scenarios, the CBS algorithm keeps about 50% of its synchronization errors within 1 ms. In comparison, the FTSP keeps less than 7% of its synchronization errors within this range. In both single-hop and multi-hop scenarios, the CBS protocol is over 3.2 times more energy-efficient than the FTSP.

Smart grid is envisioned as a critical application of cyber-physical systems and of the internet of things. In the smart grid, smart meters equipped with wireless sensors can upload meter readings (data) to smart grid control and schedule centers via the advanced metering infrastructure to improve power delivery efficiency. However, data gathered in short intervals, such as 15 minutes, will expose customers' detailed daily activities (for example, when they get up and when they use oven) using nonintrusive appliance load monitoring. Thus, data must be hidden to protect customers' privacy. However, data accountability is still required for emergency responses or to trace back suspected intrusions, even though the data is anonymous. In addition to desired security requirements, this imposes two extra tasks: Sensors in smart meters usually have resource constraints; thus, the desired security protocols have to remain lightweight in terms of computation and storage cost. Furthermore, scalability and flexibility are required since there exist vast meters. This paper presents a lightweight Privacy-aware yet Accountable Secure Scheme called PASS which guarantees privacy-aware accountability yet tackles the above challenges in the smart grid. A formal security analysis justifies that PASS can attain the security goals, while a performance analysis verifies that PASS requires few computations, and is scalable and flexible.

Navigation with sensor networks has shown many advantages and great potential in many scenarios. Previous works have mainly focused on selecting the shortest path to navigate an internal user out of an emergency field. However, they did not consider variations of the dangerous areas which usually occur in practical applications. This paper presents an efficient dynamic routing algorithm to successfully guide users to the destination exit. The navigation goal is looking for a safe and short path to enable the user to escape from a dangerous area as fast as possible. Without knowing the locations of the nodes, the user is guided by a sequence of sensor nodes to pass through the dangerous areas. The algorithm ensures the navigation path security by predicting the dynamic changes affecting the navigation path. The performance of this approach is evaluated using extensive simulations to validate its effectiveness. Simulations show that the approach is scalable and performs well in various settings.

Emergency navigation with a large number of sensors can serve as a safety service in emergencies. Recent studies have focused on navigation protocols to safely guide people to exits while helping them avoid hazardous areas. However, those approaches are not applicable in all circumstances. Both the dynamics of the environment and the mobility of users are key challenges for the efficiency and effectiveness of navigation protocols. The concepts of navigability and reachability are used to evaluate three typical navigation approaches. A large number of simulation results show that these two indicators effectively identify the performance levels of navigation protocols in changing environments.