Boon-Chong Seet

Multihop cellular networks: Technology and economics

Recently, multihop cellular networks (MCNs) were proposed to preserve the advantages of traditional single-hop cellular networks with multihop ad hoc relaying networks, while minimizing the drawbacks that they involved. In this way, MCNs enhance the performance of both the existing cellular networks and ad hoc networks. Consequently, MCN-type system is considered as a promising candidate of fourth generation (4G) wireless network for future mobile communications. This paper surveys a number of MCN-type architectures in literature through a comprehensive comparison and discussion among the proposed architectures. The discussion is divided into two phases. In the first phase, we review the concept of MCN and compare the selected MCN-type architectures from a technology perspective. In the second phase, we further compare and discuss the economic perspective on the deployment of MCNs. Specifically, we focus on the economic considerations for deploying relays in MCN-type systems.

Cross-Layer Detection of Sinking Behavior in Wireless Ad Hoc Networks Using SVM and FDA

The uniqueness of security vulnerabilities in ad hoc networks has given rise to the need for designing novel intrusion detection algorithms, different from those present in conventional networks. In this work, we propose an autonomous host-based intrusion detection system for detecting malicious sinking behavior. The proposed detection system maximizes the detection accuracy by using cross-layer features to define a routing behavior. For learning and adaptation to new attack scenarios and network environments, two machine learning techniques are utilized. Support Vector Machines (SVMs) and Fisher Discriminant Analysis (FDA) are used together to exploit the better accuracy of SVM and faster speed of FDA. Instead of using all cross-layer features, features from MAC layer are associated/correlated with features from other layers, thereby reducing the feature set without reducing the information content. Various experiments are conducted with varying network conditions and malicious node behavior. The effects of factors such as mobility, traffic density, and the packet drop ratios of the malicious nodes are analyzed. Experiments based on simulation show that the proposed cross-layer approach aided by a combination of SVM and FDA performs significantly better than other existing approaches.

CRADS: Integrated Cross Layer Approach for Detecting Routing Attacks in MANETs

In ad hoc networks, the vulnerability of nodes to routing attacks is a serious concern. In this work we propose a cross-layer based routing attack detection system for ad hoc networks. Previous work that uses mostly audit trails collected from the routing protocol suffers from inadequacy of features to construct a reliable model for detecting anomalous routing behavior. On the other hand, use of linear detectors lead to very high false positives and false negatives because of the inherent non-linear nature of the feature space. In this work, we address these issues by collating features from multiple protocols at different layers and using a non-linear detector based on support vector machine (SVM). The consequent problem of computational expense of the detection process is addressed by a combination of novel data reduction techniques. Simulation results show that the performance of the proposed CRADS is far superior than conventional protocol-specific detection systems.

Opportunities for Software-Defined Networking in Smart Grid

The large-scale, heterogeneous, and distributed nature of the Smart Grid poses many challenges to be overcome from communication networking to autonomous control and management. The underlying infrastructure of Smart Grid must be efficient and reliable in transmitting large amounts of real-time data, scalable and flexible in aggregating resources, and secured and convenient in providing management interfaces to upper layer application systems. Meanwhile, the recent rapidly developing technology of Software Defined Networking (SDN) is perceived to have tremendous potential for utilization by the underlying infrastructure. By abstracting control functionalities from underlying packet forwarding hardware to an external software controller, SDN offers a high degree of flexibility for implementing novel networking solutions to improve performances of distributed systems in large, complex network environments such as Smart Grid. In this paper, three potential use cases are presented to examine the opportunities for SDN technology in Smart Grid.

Performance Analysis of Cooperative Virtual MIMO Systems for Wireless Sensor Networks

Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs.

A comparative analysis of video codecs for multihop wireless video sensor networks

Wireless video sensor networks (WVSNs) have drawn significant attention in recent years due to the advent of low-cost miniaturized cameras, which makes it feasible to realize large-scale WVSNs for a variety of applications including security surveillance, environmental tracking, and health monitoring. However, the conventional video coding paradigms are not suitable for WVSNs due to resource constraints such as limited computation power, battery energy, and network bandwidth. In this paper, we evaluated and analyzed the performance of video codecs based on emerging video coding paradigms such as distributed video coding and distributed compressive video sensing for multihop WVSNs. The main objective of this work was to provide an insight into the computational (encoding/decoding) complexity, energy consumption, node and network lifetime, processing and memory requirements, and the quality of reconstruction of these video codecs. Based on the findings, this paper also provides some guidelines for the selection of appropriate video codecs for a given WVSN application.

A Service-Oriented Mobile Social Networking Platform for Disaster Situations

This paper proposes a novel service-oriented mobile social networking platform called MS2A for disaster situations. MS2A consists of two layers: service layer and application layer. The service layer is implemented based on the service-oriented architecture (SOA) to ease application developments. By extending and composing the web services at this layer, application developers can efficiently and flexibly develop different new functions or applications for mobile disaster rescue and recovery applications. The application layer is oriented to mobile users and it integrates with functions of mobile social networks. With dynamic and automatic service collaboration support, it enables people to easily collaborate and help each other through their mobile devices in disaster situations. The results of our experiments and demonstration examples given in the paper show the feasibility and desired functionality of MS2A for relieving disaster situations with mobile devices.

An Ontology-Based Context Model for Wireless Sensor Network (WSN) Management in the Internet of Things

Wireless sensor networks (WSNs) are an enabling technology of context-aware systems. The Internet of Things (IoT), which has attracted much attention in recent years, is an emerging paradigm where everyday objects and spaces are made context-aware and interconnected through heterogeneous networks on a global scale. However, the IoT system can suffer from poor performances when its underlying networks are not optimized. In this paper, an ontology model for representing and facilitating context sharing between network entities in WSNs is proposed for the first time. The context model aims to enable optimal context-aware management of WSNs in IoT, which will also harness the rich context knowledge of IoT systems.

CARRADS: Cross layer based adaptive real-time routing attack detection system for MANETS

Routing behavior in ad hoc networks is highly transient. Thus, dynamically adapting the routing attack detection system at real-time to new attacks and changing network conditions is critical in ad hoc networks. Conventional incremental learning methods are computationally expensive for resource-constrained nodes in ad hoc networks. In this paper, we propose CARRADS, a computationally efficient methodology for adapting the intrusion detection model at real-time. The adaptation process consists of two major stages. In the first stage, the main task is to identify occurrence of new patterns in the routing control traffic and prioritize them based on their information content. The second stage of adaptation is to incrementally update the detection model using the new patterns with minimum computational overhead. CARRADS uses SVM algorithm for its superior detection abilities. However, using some innovative techniques the computational overhead of incremental update is reduced by a factor of 20 to 30 times at the cost of a negligible decrease in detection accuracy. This makes CARRADS a viable approach for real-time IDS in ad hoc networks.

Location Estimation in Wireless Sensor Networks Using Spring-Relaxation Technique

Accurate and low-cost autonomous self-localization is a critical requirement of various applications of a large-scale distributed wireless sensor network (WSN). Due to its massive deployment of sensors, explicit measurements based on specialized localization hardware such as the Global Positioning System (GPS) is not practical. In this paper, we propose a low-cost WSN localization solution. Our design uses received signal strength indicators for ranging, light weight distributed algorithms based on the spring-relaxation technique for location computation, and the cooperative approach to achieve certain location estimation accuracy with a low number of nodes with known locations. We provide analysis to show the suitability of the spring-relaxation technique for WSN localization with cooperative approach, and perform simulation experiments to illustrate its accuracy in localization.