Towards Secure, Power-Efficient and Location-Aware Mobile Computing

In the post-PC era, mobile devices will replace desktops and become the main personal computer for many people. People rely on mobile devices such as smartphones and tablets for everything in their daily lives. A common requirement for mobile computing is wireless communication. It allows mobile devices to fetch remote resources easily. Unfortunately, the increasing demand of the mobility brings many new wireless management challenges such as security, energy-saving and location-awareness. These challenges have already impeded the advancement of mobile systems. In this dissertation we attempt to discover the guidelines of how to mitigate these problems through three general communication patterns in 802.11 wireless networks. We propose a cross-section of a few interesting and important enhancements to manage wireless connectivity. These enhancements provide useful primitives for the design of next-generation mobile systems in the future.;Specifically, we improve the association mechanism for wireless clients to defend against rogue wireless Access Points (APs) in Wireless LANs (WLANs) and vehicular networks. Real-world prototype systems confirm that our scheme can achieve high accuracy to detect even sophisticated rogue APs under various network conditions. We also develop a power-efficient system to reduce the energy consumption for mobile devices working as software-defined APs. Experimental results show that our system allows the Wi-Fi interface to sleep for up to 88% of the total time in several different applications and reduce the system energy by up to 33%. We achieve this while retaining comparable user experiences. Finally, we design a fine-grained scalable group localization algorithm to enable location-aware wireless communication. Our prototype implemented on commercial smartphones proves that our algorithm can quickly locate a group of mobile devices with centimeter-level accuracy

Survey Paper: Mobility Management in Heterogeneous Wireless Networks

AbstractEver increasing user demands and development of modern communication technologies have led to the evolution of communication networks from 1st Generation (1G) network to 4G heterogeneous networks. Further, 4G with heterogeneous network environment will provide features such as, “Always Best Connected”, “Anytime Anywhere” and seamless communication. Due to diverse characteristics of heterogeneous networks such as bandwidth, latency, cost, coverage and Quality of Service (QoS) etc., there are several open and unsolved issues namely mobility management, network administration, security etc. Hence, Designing proficient mobility management to seamlessly integrate heterogeneous wireless networks with all-IP is the most challenging issue in 4G networks. Mobile IPv6 (MIPv6) developed by Internet Engineering Task Force (IETF) has mobility management for the packet-switched devices of homogeneous wireless networks. Further, mobility management of homogeneous networks depends on network related parameter i.e., Received Signal Strength (RSS). However the mobility management of heterogeneous networks, not only depends on network related parameters, but also on terminal-velocity, battery power, location information, user-user profile & preferences and service-service capabilities & QoS etc. Designing mobility management with all-IP, while, considering issues such as context of networks, terminal, user and services is the main concern of industry and researchers in the current era

Link Quality Based Power Efficient Routing Protocol (LQ-PERP)

Recent years have witnessed a growing interest in deploying infrastructure-less, self configurable, distributed networks such as Mobile AdHoc Networks (MANET) and Wireless Sensor Networks (WSN) for applications like emergency management and physical variables monitoring respectively. However, nodes in these networks are susceptible to high failure rate due to battery depletion, environmental changes and malicious destruction. Since each node operates with limited sources of power, energy efficiency is an important metric to be considered for designing communication schemes for MANET and WSN. Energy consumed by nodes in MANET or WSN can be reduced by optimizing the internode transmission power which is uniform even with dynamic routing protocols like AODV. However, the transmission power required for internode communication depends on the wireless link quality which inturn depends on various factors like received signal power, propagation path loss, fading, multi-user interference and topological changes. In this paper, link quality based power efficient routing protocol (LQ-PERP) is proposed which saves the battery power of nodes by optimizing the power during data transmission. The performance of the proposed algorithm is evaluated using QualNet network simulator by considering metrics like total energy consumed in nodes, throughput, packet delivery ratio, end-to-end delay and jitter

IF-MANET: Interoperable framework for heterogeneous mobile ad hoc networks

The advances in low power micro-processors, wireless networks and embedded systems have raised the need to utilize the significant resources of mobile devices. These devices for example, smart phones, tablets, laptops, wearables, and sensors are gaining enormous processing power, storage capacity and wireless bandwidth. In addition, the advancement in wireless mobile technology has created a new communication paradigm via which a wireless network can be created without any priori infrastructure called mobile ad hoc network (MANET). While progress is being made towards improving the efficiencies of mobile devices and reliability of wireless mobile networks, the mobile technology is continuously facing the challenges of un-predictable disconnections, dynamic mobility and the heterogeneity of routing protocols. Hence, the traditional wired, wireless routing protocols are not suitable for MANET due to its unique dynamic ad hoc nature. Due to the reason, the research community has developed and is busy developing protocols for routing in MANET to cope with the challenges of MANET. However, there are no single generic ad hoc routing protocols available so far, which can address all the basic challenges of MANET as mentioned before. Thus this diverse range of ever growing routing protocols has created barriers for mobile nodes of different MANET taxonomies to intercommunicate and hence wasting a huge amount of valuable resources. To provide interaction between heterogeneous MANETs, the routing protocols require conversion of packets, meta-model and their behavioural capabilities. Here, the fundamental challenge is to understand the packet level message format, meta-model and behaviour of different routing protocols, which are significantly different for different MANET Taxonomies. To overcome the above mentioned issues, this thesis proposes an Interoperable Framework for heterogeneous MANETs called IF-MANET. The framework hides the complexities of heterogeneous routing protocols and provides a homogeneous layer for seamless communication between these routing protocols. The framework creates a unique Ontology for MANET routing protocols and a Message Translator to semantically compare the packets and generates the missing fields using the rules defined in the Ontology. Hence, the translation between an existing as well as newly arriving routing protocols will be achieved dynamically and on-the-fly. To discover a route for the delivery of packets across heterogeneous MANET taxonomies, the IF-MANET creates a special Gateway node to provide cluster based inter-domain routing. The IF-MANET framework can be used to develop different middleware applications. For example: Mobile grid computing that could potentially utilise huge amounts of aggregated data collected from heterogeneous mobile devices. Disaster & crises management applications can be created to provide on-the-fly infrastructure-less emergency communication across organisations by utilising different MANET taxonomies

Power management algorithms for IoT platforms

The Internet of Things (IoT) is a platform that connects various electronic systems such as home appliances, vehicles, and medical devices through wired or wireless communications. Without recharging the battery of sensors and mobile systems in IoT networks, their usage time is limited. In order to improve performance with finite battery energy, power management is used to conserve the energy dissipation of sensor networks and mobile systems. This dissertation addresses power management in two categories of systems within IoT: wireless sensor networks (WSNs) and electric vehicles (EVs). For power management in WSNs, this dissertation develops an algorithm using network coding (NC). When one sender transmits multiple packets to different receivers in a WSN, an NC algorithm reduces transmissions between the sender and the receivers by encoding many packets into one packet. Consequently, the total communication energy between the sender and the receivers is decreased. For further study about real energy gains generated by NC algorithms, we develop a wireless testbed by using mobile devices. Consequently, by varying different network variables such as transmission range of a sender and the number of receivers in the testbed network, we discover network conditions where communication energy saved by NC algorithms is increased. However, NC algorithms spend operational energy overheads for algorithm execution, encoding, and decoding. Hence, our research also shows the threshold conditions where the energy saved by the NC algorithms are larger than the energy overheads with consideration of communication variables or algorithm complexity in order to identify opportunities for energy savings. For power management of EVs, this dissertation develops an energy-efficient algorithm using neural networks which can be used for power management of EVs\u27 electronic control system. Power management saves energy consumption of the electronic control system by selectively activating electronic control units (ECUs) in the system. However, the energy savings generated by the power management could be less than the energy overheads used for the selective ECU activation and deactivation. Our algorithm experiences events where energy overheads were greater than energy savings and trains neural networks for the experienced events. The neural networks forecast energy-inefficient events and conserve energy overheads based on the predicted events. Our simulation study using real driving datasets shows that the algorithm improves the energy dissipation of the electronic control system by 5% to 7%

Performance Analysis of 3G Communication Network

In this project, third generation (3G) technologies research had been carried out to design and optimization conditions for 3G network. The 3G wireless mobile communication networks are growing at an ever faster rate, and this is likely to continue in the foreseeable future. Some services such as e-mail, web browsing etc allow the transition of the network from circuit switched to packet switched operation, resulting in increased overall network performance. Higher reliability, better coverage and services, higher capacity, mobility management, and wireless multimedia are all parts of the network performance. Throughput and spectral efficiency are fundamental parameters in capacity planning for 3G cellular network deployments. This project investigates also the downlink (DL) and uplink (UL) throughput and spectral efficiency performance of the standard Universal Mobile Telecommunications system (UMTS) system for different scenarios of user and different technologies. Power consumption comparison for different mobile technology is also discussed. The analysis can significantly help system engineers to obtain crucial performance characteristics of 3G network. At the end of the paper, coverage area of 3G from one of the mobile network in Malaysia is presented

Holistic resource management in UAV-assisted wireless networks

Unmanned aerial vehicles (UAVs) are considered as a promising solution to assist terrestrial networks in future wireless networks (i.e., beyond fifth-generation (B5G) and sixth-generation (6G)). The convergence of various technologies requires future wireless networks to provide multiple functionalities, including communication, computing, control, and caching (4C), necessary for applications such as connected robotics and autonomous systems. The majority of existing works consider the developments in 4C individually, which limits the cooperation among 4C for potential gains. UAVs have been recently introduced to supplement mobile edge computing (MEC) in terrestrial networks to reduce network latency by providing mobile resources at the network edge in future wireless networks. However, compared to ground base stations (BSs), the limited resources at the network edge call for holistic management of the resources, which requires joint optimization. We provide a comprehensive review of holistic resource management in UAV-assisted wireless networks. Integrated resource management considers the challenges associated with aerial networks (such as three-dimensional (3D) placement of UAVs, trajectory planning, channel modelling, and backhaul connectivity) and terrestrial networks (such as limited bandwidth, power, and interference). We present architectures (source-UAV-destination and UAV-destination architecture) and 4C in UAV-assisted wireless networks. We then provide a detailed discussion on resource management by categorizing the optimization problems into individual or combinations of two (communication and computation) or three (communication, computation and control). Moreover, solution approaches and performance metrics are discussed and analyzed for different objectives and problem types. We formulate a mathematical framework for holistic resource management to minimize the linear combination of network latency and cost for user association while guaranteeing the offloading, computing, and caching constraints. Binary decision variables are used to allocate offloading and computing resources. Since the decision variables are binary and constraints are linear, the formulated problem is a binary linear programming problem. We propose a heuristic algorithm based on the interior point method by exploiting the optimization structure of the problem to get a sub-optimal solution with less complexity. Simulation results show the effectiveness of the proposed work when compared to the optimal results obtained using branch and bound. Finally, we discuss insight into the potential future research areas to address the challenges of holistic resource management in UAV-assisted wireless networks