Performance Prediction and Tuning for Symmetric Coexistence of WiFi and ZigBee Networks

Due to the explosive deployment of WiFi and ZigBee wireless networks, 2.4GHz ISM bands (2.4GHz-2.5GHz) are becoming increasingly crowded, and the co-channel coexistence of these two networks is inevitable. For coexistence networks, people always want to predict their performance (e.g. throughput, energy consumption, etc.) before deployment, or even want to tune parameters to compensate unnecessary performance degradation (owing to the huge differences between these two MAC protocols) or to satisfy some performance requirements (e.g., priority, delay constraint, etc.) of them. However, predicting and tuning performance of coexisting WiFi and ZigBee networks has been a challenging task, primarily due to the lack of corresponding simulators and analytical models. In this dissertation, we addressed the aforementioned problems by presenting simulators and models for the coexistence of WiFi and ZigBee devices. Specifically, based on the energy efficiency and traffic pattern of three practical coexistence scenarios: disaster rescue site, smart hospital and home automation. We first of all classify them into three classes, which are non-sleeping devices with saturated traffic (SAT), non-sleeping devices with unsaturated traffic (UNSAT) and duty-cycling devices with unsaturated traffic (DC-UNSAT). Then a simulator and an analytical model are proposed for each class, where each simulator is verified by simple hardware based experiment. Next, we derive the expressions for performance metrics like throughput, delay etc., and predict them using both the proposed simulator and the model. Due to the higher accuracy of the simulator, the results from them are used as the ground truth to validate the accuracy of the model. Last, according to some common performance tuning requirements for each class, we formulate them into optimization problems and propose the corresponding solving methods. The results show that the proposed simulators have high accuracy in performance prediction, while the models, although are less accurate than the former, can be used in fast prediction. In particular, the models can also be easily used in optimization problems for performance tuning, and the results prove its high efficiency

Achieving reliable and enhanced communication in vehicular ad hoc networks (VANETs)

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirement for the degree of Doctor of PhilosophyWith the envisioned age of Internet of Things (IoTs), different aspects of Intelligent Transportation System (ITS) will be linked so as to advance road transportation safety, ease congestion of road traffic, lessen air pollution, improve passenger transportation comfort and significantly reduce road accidents. In vehicular networks, regular exchange of current position, direction, speed, etc., enable mobile vehicle to foresee an imminent vehicle accident and notify the driver early enough in order to take appropriate action(s) or the vehicle on its own may take adequate preventive measures to avert the looming accident. Actualizing this concept requires use of shared media access protocol that is capable of guaranteeing reliable and timely broadcast of safety messages. This dissertation investigates the use of Network Coding (NC) techniques to enrich the content of each transmission and ensure improved high reliability of the broadcasted safety messages with less number of retransmissions. A Code Aided Retransmission-based Error Recovery (CARER) protocol is proposed. In order to avoid broadcast storm problem, a rebroadcasting vehicle selection metric η, is developed, which is used to select a vehicle that will rebroadcast the received encoded message. Although the proposed CARER protocol demonstrates an impressive performance, the level of incurred overhead is fairly high due to the use of complex rebroadcasting vehicle selection metric. To resolve this issue, a Random Network Coding (RNC) and vehicle clustering based vehicular communication scheme with low algorithmic complexity, named Reliable and Enhanced Cooperative Cross-layer MAC (RECMAC) scheme, is proposed. The use of this clustering technique enables RECMAC to subdivide the vehicular network into small manageable, coordinated clusters which further improve transmission reliability and minimise negative impact of network overhead. Similarly, a Cluster Head (CH) selection metric ℱ(\u1d457) is designed, which is used to determine and select the most suitably qualified candidate to become the CH of a particular cluster. Finally, in order to investigate the impact of available radio spectral resource, an in-depth study of the required amount of spectrum sufficient to support high transmission reliability and minimum latency requirements of critical road safety messages in vehicular networks was carried out. The performance of the proposed schemes was clearly shown with detailed theoretical analysis and was further validated with simulation experiments

Towards Real-time Wireless Sensor Networks

Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system

Real-time Power Aware Routing in Wireless Sensor Networks

Many mission-critical wireless sensor network applications must resolve the inherent conflict between the tight resource constraints on each sensor node, particularly in terms of energy, with the need to achieve desired quality of service such as end-to-end real-time performance. To address this challenge we propose the Real-time Power-Aware Routing (RPAR) protocol. RPAR achieves required communication delays at minimum energy cost by dynamically adapting the transmission power and routing decisions based on packet deadlines. RPAR integrates a geographic forwarding policy cognizant of deadlines, power, and link quality with new algorithms for on-demand power adaptation and efficient neighborhood discovery. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadline misses and energy consumption when compared to existing real-time and energy-efficient routing protocols and beacon based neighborhood management schemes

Utilizing ZigBee Technology for More Resource-efficient Wireless Networking

Wireless networks have been an essential part of communication in our daily life. Targeted at different applications, a variety of wireless networks have emerged. Due to constrained resources for wireless communications, challenges arise but are not fully addressed. Featured by low cost and low power, ZigBee technology has been developed for years. As the ZigBee technology becomes more and more mature, low-cost embedded ZigBee interfaces have been available off the shelf and their sizes are becoming smaller and smaller. It will not be surprising to see the ZigBee interface commonly embedded in mobile devices in the near future. Motivated by this trend, we propose to leverage the ZigBee technology to improve existing wireless networks. In this dissertation, we classify wireless networks into three categories (i.e., infrastructure-based, infrastructure-less and hybrid networks), and investigate each with a representative network. Practical schemes are designed with the major objective of improving resource efficiency for wireless networking through utilizing ZigBee technology. Extensive simulation and experiment results have demonstrated that network performance can be improved significantly in terms of energy efficiency, throughput, packet delivery delay, etc., by adopting our proposed schemes

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Ph.DDOCTOR OF PHILOSOPH

Stochastig modeling with continuous feedback markov fluid queues

Cataloged from PDF version of article.Markov fluid queues (MFQ) are systems in which a continuous-time Markov chain determines the net rate into (or out of ) a buffer. We deal with continuous feedback MFQs (CFMFQ) for which the infinitesimal generator of the background process and the drifts in each state are allowed to depend on the buffer level through continuous functions. Explicit solutions of CFMFQs for a few special cases has been reported, but usually numerical methods are preferred. A numerically stable solution method based on ordered Schur decomposition is already known for multi-regime MFQs (MRMFQ). We propose a framework for approximating CFMFQs by MRMFQs via discretizing the buffer space. The parameters of the CFMFQ are approximated by piecewise constant functions. Then, the solution is obtained by block-tridiagonal LU decomposition for the related MRMFQ. Moreover, we describe a numerical method that enables us to solve large scale systems efficiently. We model basically two different stochastic systems with CFMFQs. The first is the workload-bounded MAP/PH/1 queue, to which the arrivals occur according to a workload-dependent MAP (Markovian Arrival Process), and the arriving job size distribution is phase-type. The jobs that would cause the buffer to overflow are rejected partially or completely. Also, the service speed is allowed to depend on the buffer level. As the second application, we model the horizon-based delayed reservation mechanism in Optical Burst Switching networks with or without fiber delay lines. We allow multiple traffic classes and the effect of offset-based and FDL-based differentiation among traffic classes in terms of burst blocking is investigated. Lastly, we propose a distributed algorithm for air-time fairness in multi-rate WLANs that overcomes the performance anomaly in IEEE 802.11 WLANs. We also give a stochastic model of the proposed model, and provide a novel and elaborate proof for its effectiveness. We also present an extensive simulation study.Yazıcı, Mehmet AkifPh.D