Samih Abdul-Nabi

Reducing energy consumption in cellular networks by adjusting transmitted power of base stations

With the growth of cellular networks and emergence of new technologies, the power consumption of mobile communication networks has become an important and worrying topic that should be taken into consideration in any future cellular evolution. Recently, many solutions were proposed in the literature to reduce the power in cellular communications while maintaining the quality of service, in the purpose of achieving, what is known now as “Green Communications”. In this paper, we are interested in power-efficient methods altering the transmitted power of base stations, especially Sleep Mode and Cell Zooming techniques. After presenting the advantages, drawbacks and implementations of these two green solutions, we will introduce a new algorithm that should be implemented and applied on the base stations to reduce their total power consumption. This algorithm considers several cases including Cell Zooming and combination of Sleep Mode and Cell Zooming depending on the cell loads and mobile distribution. It also computes the power needed in each case and then chooses the most power-efficient scenario. Moreover, we will study the performance and efficacy of implementing our algorithm in some practical cellular network settings.

Efficient Network Coding packet selection model for QoS-based applications

In this paper, we study Network Coding (NC) at switching level. We use a novel NC algorithm to select, among received packets, those to be coded and released into the network. The selection is based on address correlation and QoS is attained based on delay optimization. The main feature of our algorithm is that it enhances the coding decision and guarantees decodability of transmitted packets. We developed a testing model to evaluate the performance of our proposed algorithm. Significant throughput and QoS improvements can be observed when our algorithm is compared with traditional NC schemes.

AES algorithm implementation for a simple low cost portable 8-bit microcontroller

Encryption has become a critical need for almost every data communication systems. A huge value of sensitive data is transferred daily via different computer networks such as electronic banking, email applications and file exchange. Advanced Encryption Standard (AES) algorithm has become the optimum choice for various security services in numerous applications like Ad hoc networks and wireless sensor networks, which does not require high computing capacity, memory requirements, less power consumption. Therefore, many researches focus on this type of algorithm in order to improve its efficiency and performance. This paper deals with the challenge of implementing the AES algorithm on 8-bit microcontrollers that provides a low cost, fast and portable hardware key that guarantees the confidentiality, integrity and avoiding key exchange via unsecured channel that imposes a real thread on any symmetric algorithm.

Aging in Network Coding

With network coding, received packets are linearly combined together and broadcasted over the network. Several techniques exist in the literature dedicated to the process of combining packets. However, these techniques focus on forwarding and decoding coded packets without taking into consideration the life cycle of each individual packet. By neglecting this issue, a packet might live forever in coded messages introducing an overhead on the coding/decoding process. In this letter, we introduce the concept of aging that limits the existence of a packet within coded messages. Statistics about the effect of aging on the size of coded messages are provided in order to determine the best tradeoff between the number of required transmissions and then the throughput gain on one hand and the buffering size and then the decoding complexity on the other hand.

RSSI range estimation for indoor anchor based localization for wireless sensor networks

Range estimation using RSSI (received signal strength indicator) for localization application for wireless sensor networks is a challenging task. Interference from the shared 2.4GHz channel and fading due to multipath propagation and shadowing deteriorate the process of range estimation. In this work an estimation of these noise levels that are present in the environment is being carried out by anchor nodes which are placed throughout the sensing field. These anchor nodes will compare the actual distance between them with distance computed from the measured RSSI. Four different techniques have been devised that applies a smoothing coefficient on the measured RSSI taking into consideration information about the environment from the anchor nodes. Simulation shows that even when the error introduced is equivalent to 100% of the transmission range, the error in range estimation was around 25%.

Novel distributed decoding scheme for efficient resource utilization in network coding

In this paper, we introduce network coding (NC) at intermediate nodes of a linear network where coding is conducted on address correlated packets. In particular, we propose a novel algorithm for decoding network-coded messages that enhances the bandwidth usage and reduces the resource allocation by allowing nodes in the network to perform distributed decoding. We show that, compared to traditional decoding at end nodes, distributed decoding allows reduction not only in the number of transmitted bytes but also in the number of resources needed to perform NC. Our strategy is compared to decoding at end nodes and experiments show a reduction of 64% in the number of transmitted bytes and a reduction of 93% of buffering time when using distributed decoding to exchange 1000 packets between end nodes of a linear network of 8 nodes.

Low-cost dry swimming machine using Kinect biomotion capture

A dry swimming machine is a machine that allows swim training or exercise on dry land. Few dry swimming machines are commercially available for specialized swim training and stroke style evaluation. These machines are usually expensive and not designed or made suitable for physical exercise. Most of these devices are sensor based. Few high-end swimming machines have been developed and customized for the motion picture industry are based on biomotion capture (mocap). These devices are very expensive and not commercially available. In 2010, Microsoft introduced “Kinect”, which is a line of motion sensing input devices for Xbox video game consoles and Windows PCs. The device features an RGB camera, depth sensor, microphones, and proprietary software, which provide full-body 3D motion capture, facial recognition and voice recognition capabilities. This study takes advantage of this technology to build a low-cost swimming machine with motion capture capabilities. The skeletal motion captured using the Kinect camera is streamed to a Matlab routine and analyzed to control a motor designed to lift the swimmer, depending on their swimming technique and performance compared to a professional swimmer data saved in a database.

Secure localization for wireless sensor networks using decentralized dynamic key generation

Security frameworks for wireless sensor network localization application can no longer be ignored. Wireless sensor network are being deployed in sensitive environment that require high levels of confidentiality, integrity and authenticity. Employing already existing security algorithms dedicated for wireless networks are infeasible for sensor network environment due to limited resources. In this context, a security framework tailored for wireless sensor network localization applications is proposed. The algorithm uses symmetric key encryption where the keys are generated in a decentralized fashion. These keys are computed on the fly, never transmitted and, changes autonomously with each transmission. Furthermore, the algorithm utilizes the bitwise XOR function for all its encryption needs which presents low overhead. Simulations show the robustness of the proposed algorithm in case of malicious node attack on the localization process and on key deduction and computation.

Optimizing Context-Aware Resource and Network Assignment in Heterogeneous Wireless Networks

This paper discusses the problem of user association and downlink resource allocation in heterogeneous wireless networks (HWNs) where a mobile node (MN) can associate to a single network at a time. A context-aware optimization problem is formulated to maximize the aggregate user-centric profit in the system while taking into consideration the network constraints, user preferences, and the amount of data rate requested by each MN. To achieve its purpose, the formulated problem employs contextual information related to the MN measurements and requirements, the HWN architecture, and the available resources at each network. The user-centric profit is based on the quality of the received signal and the power consumption at the MN. The formulated optimization problem is discrete (binary) with high complexity; based on the continuous relaxation of the problem, a solution with polynomial-time complexity is proposed. It is shown through simulations that the proposed solution achieves a nearoptimal performance in terms of average user-centric profit and percentage of blocked data rate. Moreover, the proposed solution requests lower number of handovers.

Load-aware power efficiency maximization in heterogeneous wireless networks

This paper proposes a solution to maximize the power efficiency, i.e. datarate per power unit, in a heterogeneous wireless system that is based on integrated mobile base stations (BSs) and Wi-Fi access points (APs). In this context, a user association and downlink resource allocation optimization problem is formulated. The formulated problem considers the power consumption at both networks and mobile terminals (MTs), and the data rate requirement, i.e. load, of each MT. Since MTs could only be associated with a single network at a time, the formulated problem is binary with high complexity. Thus, a new sub-optimal solution with polynomial-time complexity is proposed based on the continuous relaxation of the problem. Simulation results show that the proposed sub-optimal solution, when compared to the trivial network selection methodology, remarkably reduces the power consumption of networks and MTs. Moreover, it is shown that the proposed solution performs close to the optimal one.