There has been a quick development in the wireless network area during the last decade. Mostly these days the focus in the wireless area is on very high speed and long range applications. This thesis describes how ZigBee is suitable for wireless sensor networks in logistic telemetry applications for global managing and monitoring of goods. ZigBee has been developed by the organization named as ‘ZigBee Alliance’ as a new wireless standard for the wireless solutions based upon the IEEE 802.15.4 Standard [2]. ZigBee is a new technology as compared to the other wireless technologies such as Bluetooth, but it has certain characteristics such as low cost, low power, support for mesh networking e.t.c which makes its chances to be more successful than others. The other aim of this thesis is to examine different issues related to ZigBee to see its fitness for logistic telemetry applications like multi-hop routing issues, routing strategies and design requirements. ZigBee is relatively new wireless technology, so there are great deals of promises associated with it. In this thesis, a comparison between ZigBee and Bluetooth technologies will also be made.

X3 C is a Swedish company which develops a world wide good tracking system by using ARFID tags placed on every item which has to be delivered and base stations as gateway in a wireless sensor network. The requirement of a long lifespan of their ARFID tags made it difficult to implement security. Firstly an evaluation of possible security mechanisms and their power consumption was done by measuring the avalanche effect and character frequency of the sym- metric algorithms Blowfish, RC2 and XTEA. Secondly, the required CPU time which is needed by each algorithm for encrypting a demo plaintext, was measured and analyzed. Summariz- ing both analysis, the XTEA algorithm, run in CBC mode, is the recommendation for the XC ARFID tags. The testing processes and the results are presented in detail in this thesis.

Multi-hop wireless network are promising techniques in the field of wireless communication. The dynamic topology of the network and the independent selfish participants of the network make it difficult to be modeled by traditional tools. Game theory is one of the most powerful tools for such problems. However, most current works have certain limitations. There has not been widely accepted solution for the problem yet. In this thesis we propose our solutions for the problem of bandwidth sharing in wireless networks. We assume the nodes are rational, selfish but not malicious independent agents in the game. In our model, nodes are trying to send their data to the access point. Some nodes may require others to forward their package to successfully connect to the access point. However, nodes are selfish and do not wish to help others. Therefore it is possible that some nodes may refuse the requirement. In that case, the unpleasant nodes may punish the others by slowing down their traffic, in which case both parties will suffer. Therefore it is non-trivial to find out the Equilibrium for these nodes after the bargain process. What is the proper distribution of resources among these nodes? We propose a solution based on the game theory. Our solution fulfils the goal of fairness and social welfare maximum.

Scheduling in wireless networks plays an important role. The undeterministic nature of the wireless channel is usually considered as an undesirable property. Recently, the idea of opportunistic scheduling is introduced and it takes advantage of the time-varying channel for performance improvement such as throughput and delay. Since the introduction of opportunistic scheduling, there are two main bodies of works. The first body of works assume that each user is greedy and has infinite backlog for transfer. With this assumption, fairness objective becomes an important factor in designing a scheduling algorithm to avoid severe starvation of certain users. Typical fairness involve processor sharing time fairness, proportional fairness, and minimum performance guarantee. On the other hand, delay performance is not a appropriate factor to evaluate the effectiveness of a scheduling algorithm because of the infinite backlog assumption. In reality, this assumption is not true as data arrives and leaves the network randomly in practice. The second body of works deal with the relaxation of the infinite backlog assumption. Thus, the notion of stability region arises. The definition of stability is that the queue at each source node remains finite. Stability region can be defined as the set of traffic intensities which can all be stabilized by the network. The well known throughput optimal algorithm is proven capable of achieving the largest stability region. In this thesis, two innovative opportunistic scheduling algorithms which aim to minimize the amount of resources used to stabilize the current traffics are proposed. The key feature of our algorithm is that the incoming traffic rates are available to the scheduler, whereas the throughput optimal algorithm has no such prior traffic knowledge. Performance comparisons are made by means of simulation to demonstrate that the proposed algorithms can achieve the same stability region as the throughput optimal algorithm. Moreover, the delay performance is better than that of the throughput optimal algorithm, especially under heavy traffic conditions.

In this thesis, we propose a scheduling problem for the downlink of a single cell system with multiple sectors. We formulate an optimization problem based on a generalized round robin scheme that aims at minimizing the cycle length necessary to provide one timeslot to each user, while avoiding harmful interference. Since this problem is under-constrained and might have multiple solutions, we propose a second optimization problem for which we try to find a scheduling that minimizes the cycle length while being as efficient as possible in resource utilization. Both of these problems are large integer programming problems that can be solved numerically using a commercial solver, but for real time use, efficient heuristics need to be developed. We design heuristics for these two problems and validate them by comparing their performances to the optimal solutions.

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own.

This thesis focuses on three fundamental issues that concern data aggregation protocols for periodic data collection in sensor networks: <i>which</i> sensor nodes should report their data, <i>when</i> should they report it, and should they use <i>unicast</i> or <i>broadcast</i> based protocols for this purpose. <p> The issue of when nodes should report their data is considered in the context of real-time monitoring applications. The first part of this thesis shows that asynchronous aggregation, in which the time of each nodes transmission is determined adaptively based on its local history of past packet receptions from its children, outperforms synchronous aggregation by providing lower delay for a given end-to-end loss rate. <p> Second, new broadcast-based aggregation protocols that minimize the number of packet transmissions, relying on multipath delivery rather than automatic repeat request for reliability, are designed and evaluated. The performance of broadcast-based aggregation is compared to that of unicast-based aggregation, in the context of both real-time and delay-tolerant data collection. <p> Finally, this thesis investigates the potential benefits of dynamically, rather than semi-statically, determining the set of nodes reporting their data, in the context of applications in which coverage of some monitored region is to be maintained. Unicast and broadcast-based coverage-preserving data aggregation protocols are designed and evaluated. The performance of the proposed protocols is compared to that of data collection protocols relying on node scheduling.

As a result of rapid progress in research and development, today's wireless world exhibits several heterogeneous communication networks, such as cellular networks, satellite networks, wireless local area networks (WLAN), mobile ad hoc networks (MANET), and sensor networks. These networks are complementary to each other. Hence, their integration can realize a unified wireless system that has the best features of the individual networks. This has spurred much research interest in designing integrated next-generation of wireless systems (NGWS). While existing wireless networks have been extensively studied individually, the integrated wireless system brings new challenges in architecture design, system management, and protocol design. The different wireless networks use different communication technologies and are based on different networking paradigms. Therefore, it is challenging to integrate these networks such that their heterogeneities are hidden from each other and a harmonious inter-operation among them is achieved. The objective of this research is to design a scalable, secure, and robust architecture and to develop seamless mobility management protocols for NGWS. More specifically, an architecture that integrates the heterogeneous wireless systems is first proposed for NGWS. Next, a cross-layer (Layer 2 + 3) handoff management protocol is developed for NGWS. Afterward, analytical modeling is developed to investigate the handoff performance of the existing mobility management protocols for different types of applications. Finally, a framework for multi-layer mobility management is developed to support the seamless handoff support to all types of applications in NGWS.

IEEE 802.11 wireless networks are plagued with problems of unauthorized access. Left undetected, unauthorized access is the precursor to additional mischief. Current approaches to detecting intruders are invasive or can be evaded by stealthy attackers. We propose the use of spectral analysis to identify the type of wireless network interface card (NIC). This mechanism can be applied to support the detection of unauthorized systems that use NICs which are different from that of a legitimate system. We focus on two functions, active scanning and dynamic rate switching, required by the 802.11 standard that are implemented in the hardware and software of the wireless NIC. We show that the implementation of these functions influence the transmission patterns of a wireless stream that are observable through traffic analysis. Furthermore, differences in the behavior of a wireless stream caused by differences in the implementation of these functions are exploited to establish the identity of a NIC. Our mechanism for NIC identification uses signal processing to analyze the periodicity embedded in the wireless traffic caused by active scanning and rate switching. A spectral profile is created from the periodic components of the traffic and used for the identity of the wireless NIC. We show that we can discern between NICs manufactured by different vendors and NICs within the same manufacturer using the spectral profile.

The thesis focuses on resource management or sensor allocation when we use bearings-only measurements to track targets in an unattended ground sensor (UGS) network. Intelligent resource management is necessary because each UGS sensor node has limited power and it is desirable that estimation performance not degrade very much when only a few nodes are active to maximize the effective tracking lifetime. For scheduling to prolong the tracking lifetime, a new energy-based (EB) metric is proposed to model the number of snapshots remaining for a hypothesized node set, i.e., the remaining battery energy divided by the energy to sense and share information amongst the node set. Unlike other methods that use the total energy consumed for the given snapshot as the energy-based metric, the new EB metric can achieve load balancing of the nodes without resorting to computationally demanding non-myopic optimization. The metrics to choose nodes at a given snapshot could be geometry-based (GB) to minimize the estimation error, EB, or multiobjective. In determining the active set, each node only knows the existence of itself, the active set of nodes from the previous snapshot and the node's neighbors, i.e., the set of nodes within a distance of r_nei. When measuring the tracking lifetime of the system, we propose an adaptive transmission range control, known as the knowledge pool (KP) where the transmission range is determined by the knowledge of the network and the currently remaining battery level. The KP saves more energy usage than another adaptive transmission range control bounded with the GB metric when the global location information is available. We also provide practical search algorithms to optimize a constraint metric (multiobjective function) using one metric as the optimization metric under the constraint of the other. We also demonstrate the resource management schemes for multitarget tracking with the field data.