In a distributed parameter estimation problem, during each sampling instant, a typical sensor node communicates its estimate either by the diffusion algorithm or by the incremental algorithm. Both these conventional distributed algorithms involve significant communication overheads and, consequently, defeat the basic purpose of wireless sensor networks. In the present paper, we therefore propose two new distributed algorithms, namely, block diffusion least mean square (BDLMS) and block incremental least mean square (BILMS) by extending the concept of block adaptive filtering techniques to the distributed adaptation scenario. The performance analysis of the proposed BDLMS and BILMS algorithms has been carried out and found to have similar performances to those offered by conventional diffusion LMS and incremental LMS algorithms, respectively. The convergence analyses of the proposed algorithms obtained from the simulation study are also found to be in agreement with the theoretical analysis. The remarkable and interesting aspect of the proposed block-based algorithms is that their communication overheads per node and latencies are less than those of the conventional algorithms by a factor as high as the block size used in the algorithms.

T. Panigrahi

P. M. Pradhan

G. Panda

B. Mulgrew

Block Least Mean Squares Algorithm over Distributed Wireless Sensor Network

With the exploding power consumption in private households and increasing environmental and regulatory restraints, the need to improve the overall efficiency of electrical networks has never been greater. That being said, the most efficient way to minimize the power consumption is by voluntary mitigation of home electric energy consumption, based on energy-awareness and automatic or manual reduction of standby power of idling home appliances. Deploying bi-directional smart meters and home energy management (HEM) agents that provision real-time usage monitoring and remote control, will enable HEM in &#8220;smart households.&#8221; Furthermore, the traditionally inelastic demand curve has began to change, and these emerging HEM technologies enable consumers (industrial to residential) to respond to the energy market behavior to reduce their consumption at peak prices, to supply reserves on a as-needed basis, and to reduce demand on the electric grid. Because the development of smart grid-related activities has resulted in an increased interest in demand response (DR) and demand side management (DSM) programs, this paper presents some popular DR and DSM initiatives that include planning, implementation and evaluation techniques for reducing energy consumption and peak electricity demand. The paper then focuses on reviewing and distinguishing the various state-of-the-art HEM control and networking technologies, and outlines directions for promoting the shift towards a society with low energy demand and low greenhouse gas emissions. The paper also surveys the existing software and hardware tools, platforms, and test beds for evaluating the performance of the information and communications technologies that are at the core of future smart grids. It is envisioned that this paper will inspire future research and design efforts in developing standardized and user-friendly smart energy monitoring systems that are suitable for wide scale deployment in homes.

Aravind Kailas

Valentina Cecchi

Arindam Mukherjee

A Survey of Communications and Networking Technologies for Energy Management in Buildings and Home Automation

We introduce an improved image transmission scheme over wireless channels with flat Rayleigh
fading. The proposed scheme jointly optimizes bit power and modulation level to maximize the peak signal-to-noise
ratio (PSNR) of the reconstructed image and hence improves the perceptual quality of the received image. In
this optimization process, the significance of bits with regard to the overall quality of the image is exploited. The
optimality of the proposed algorithm is demonstrated using the Lagrange method and verified through an iterative
offline exhaustive search algorithm. For practical implementation, a look-up table is used at the transmitter for
assigning the bit power and modulation level to each bit stream according to the received signal-to-noise ratio
(SNR) observed at the receiver. The proposed scheme has low complexity since the look-up table is computed offline, only once, and used for any image which makes it suitable for devices with limited processing capability.
Analytical and simulation results show that the proposed scheme with jointly optimized bit power and variable
modulation level provides an improvement in PSNR of about 10 to 20 dB over fixed power fixed modulation
(16-QAM). A further reduction in complexity is achieved by using the average signal-to-noise ratio rather than the
instantaneous SNR in selecting the system parameters.

Mohamed El-Tarhuni

Mohamed Hassan

Akram Bin Sediq

A Jointly Optimized Variable M-QAM and Power Allocation Scheme for Image Transmission

One of the efficient ways to transmit high data rate is by employing a multiple-input multiple-output (MIMO) transmission. One of the MIMO schemes, known as spatial multiplexing (SM), relies on the linear independence data streams from different transmit antennas to exploit the capacity from the fading channels. Consequently, SM suffers from the effect of spatial correlation which is the limiting factor in achieving the capacity benefit that SM can offer. In an attempt to increase the robustness of the SM transmission in a wide range of correlated channels, the use of dynamic subcarrier allocation (DSA) is investigated. The effective signal-to-interference-and-noise ratio (SINR) metric is used as the performance metric to determine the subcarrier quality which can then be utilised in the allocation. Two novel variants of the subcarrier allocation scheme are proposed. It is shown that the DSA-SINR approach improves the BER performance of SM transmission in highly correlated channels environment.

Rosdiadee Nordin

An Investigation of Self-Interference Reduction Strategy in a Spatially Correlated MIMO Channel

Deployment of a large number of femtocells to jointly provide coverage in an enterprise environment raises critical challenges especially in future self-organizing networks which rely on plug-and-play techniques for configuration. This paper proposes a multi-objective heuristic based on a genetic algorithm for a centralized self-optimizing network containing a group of UMTS femtocells. In order to optimize the network coverage in terms of handled load, coverage gaps, and overlaps, the algorithm provides a dynamic update of the downlink pilot powers of the deployed femtocells. The results demonstrate that the algorithm can effectively optimize the coverage based on the current statistics of the global traffic distribution and the levels of interference between neighboring femtocells. The algorithm was also compared with the fixed pilot power scheme. The results show over fifty percent reduction in pilot power pollution and a significant enhancement in network performance. Finally, for a given traffic distribution, the solution quality and the efficiency of the described algorithm were evaluated by comparing the results generated by an exhaustive search with the same pilot power configuration.

Lina S. Mohjazi

Mahmoud A. Al-Qutayri

Hassan R. Barada

Kin F. Poon

Raed M. Shubair

Self-Optimization of Pilot Power in Enterprise Femtocells Using Multi objective Heuristic

The constraint of a wireless network has motivated many researchers to develop network-aware applications that can dynamically adjust the users&#39; demand based on network resources. For this to happen, applications need to have some mechanism that can estimate the network bandwidth by simply adjusting their behavior based on the collected network characteristics information. In the past, there have been several proposals that provide passive and active bandwidth estimation approaches for wired and wireless network. However, little effort has been spent to address the crucial issues of reliability and congestion control especially in a wireless network environment, which stay as a sticking point for the success of network-aware application. This paper focuses on providing accurate, low-intrusiveness, and fast-convergence time bandwidth estimation for network-aware application architecture. The experimental results validate the efficiency of the proposed solution in terms of accuracy, intrusiveness, and timelines.

Mohd Faisal Ibrahim

Masita Jamal

Saadiah Yahya

Mohd Nasir Taib

Available Bandwidth Estimation in Network-Aware Applications for Wireless Campus e-Learning System

CAC (Call Admission Control) plays a significant role in providing QoS (Quality of Service) in mobile wireless networks. In addition to much research that focuses on modified Mobile IP to get better efficient handover performance, CAC should be introduced to Mobile IP-based network to guarantee the QoS for users. In this paper, we propose a CAC scheme which incorporates multiple traffic types and adjusts the admission threshold dynamically using fuzzy control logic to achieve better usage of resources. The method can provide QoS in Mobile IPv6 networks with few modifications on MAP (Mobility Anchor Point) functionality and slight change in BU (Binding Update) message formats. According to the simulation results, the proposed scheme presents good performance of voice and video traffic at the expenses of poor performance on data traffic. It is evident that these CAC schemes can reduce the probability of the handoff dropping and the cell overload and limit the probability of the new call blocking.

Jung-Shyr Wu

Shun-Fang Yang

Chen-Chieh Huang

Admission Control for Multiservices Traffic in Hierarchical Mobile IPv6 Networks by Using Fuzzy Inference System

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Journal of Computer Networks and Communications publishes original research and review articles that investigate both the theoretical and practical aspects of computer networks and communications.

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Journal of Computer Networks and Communications