Many modern communication networks suffer significantly from the unreliable characteristic of their nodes and links. To deal with failures, traditionally, centralized erasure codes have been extensively used to improve reliability by introducing data redundancy. In this thesis, we address several issues in implementing erasure codes in a decentralized way such that coding operations are spread to multiple nodes. Our solutions are based on fountain codes and randomized network coding, because of their capability of being amenable to decentralized implementation originated from their simplicity and randomization properties. Our contributions consist of four parts. First, we propose a novel decentralized implementation of fountain codes utilizing random walks. Our solution does not require node location information and enjoys a small local routing table with a size in proportion to the number of neighbors. Second, we introduce priority random linear codes to achieve partial data recovery by partition and encoding data into non-overlapping or overlapping subsets. Third, we present geometric random linear codes to decrease communication costs in decoding significantly, by introducing modest data redundancy in a hierarchical fashion. Finally, we study the application of network coding in disruption tolerant networks. We show that network coding achieves shorter data transmission time than replication, especially when data buffers are limited. We also propose an efficient variant of network coding based protocol, which attains similar transmission delay, but with much lower transmission costs, as compared to a protocol based on epidemic routing.

Many modern communication networks suffer significantly from the unreliable characteristic of their nodes and links. To deal with failures, traditionally, centralized erasure codes have been extensively used to improve reliability by introducing data redundancy. In this thesis, we address several issues in implementing erasure codes in a decentralized way such that coding operations are spread to multiple nodes. Our solutions are based on fountain codes and randomized network coding, because of their capability of being amenable to decentralized implementation originated from their simplicity and randomization properties. Our contributions consist of four parts. First, we propose a novel decentralized implementation of fountain codes utilizing random walks. Our solution does not require node location information and enjoys a small local routing table with a size in proportion to the number of neighbors. Second, we introduce priority random linear codes to achieve partial data recovery by partition and encoding data into non-overlapping or overlapping subsets. Third, we present geometric random linear codes to decrease communication costs in decoding significantly, by introducing modest data redundancy in a hierarchical fashion. Finally, we study the application of network coding in disruption tolerant networks. We show that network coding achieves shorter data transmission time than replication, especially when data buffers are limited. We also propose an efficient variant of network coding based protocol, which attains similar transmission delay, but with much lower transmission costs, as compared to a protocol based on epidemic routing.

Web browsing via Wi-Fi wireless access networks has become a basic function on a variety of consumer mobile electronic devices, such as smart phones, PDAs, and the Apple iPad. It has been found that in terms of energy consumption, wireless communications/networking plays an important role in mobile devices. Since the power-saving mode (PSM) of the IEEE 802.11 a/b/g standard is not tailored for the HTTP protocol, we propose a novel power saving scheme that exploits the characteristics of web applications. After sending HTTP requests, the proposed power saving scheme updates the estimated value of RTT based on the information contained in the TCP timestamp header field. Next, the proposed scheme adjusts the value of the listening period based on the estimated value of RTT. When all TCP connections have been closed, the wireless network card could enter the deep-sleeping mode. In this case, the value of the listening period could be larger than one second, since the user is reading the webpage and is unlikely to send another HTTP request within one second. The usage of the deep-sleeping mode can significantly reduce the power consumption of mobile devices.

No description available.

Communication in wireless networks elementally comprises of packet exchanges over individual wireless links and routes formed by these links. To this end, two problems are fundamental: assessment of link quality and identification of the least-cost (optimal) routes. However, little is known about achieving these goals without incurring additional overhead to IEEE 802.11 networks. In this thesis, I design and experimentally evaluate two frameworks that enable individual 802.11 nodes to characterize their wireless links and routes by employing only local and passively collected information. First, I enable 802.11 nodes to assess their links by characterizing packet delivery failures and failure causes. The key problem is that nodes cannot individually observe many factors that affect the packet delivery at both ends of their links and in both directions of 802.11 communication. To this end, instead of relying on the assistance of other nodes, I design the first practical framework that extrapolates the missing information locally from the nodes' overhearing, the observable causal relationships of 802.11 operation and characterization of the corrupted and undecodable packets. The proposed framework employs only packet-level information generally reported by commodity 802.11 wireless cards. Next, I design and evaluate routing primitives that enable individual nodes to suppress their poor route selections. I refer to a route selection as poor whenever the employed routing protocol fails to establish the existing least-cost path according to an employed routing metric. This thesis shows that an entire family of the state-of-the art on-demand distance-vector routing protocols, including the standards-proposed protocol for IEEE 802.11s mesh networks, suffers from frequent and long-term poor selections having arbitrary path costs. Consequently, such selections generally induce severe throughput degradations for network users. To address this problem, I design mechanisms that identify optimal paths locally by employing only the information readily available to the affected nodes. The proposed mechanisms largely suppress occurrence of inferior routes. Even when such routes are selected their durations are reduced by several orders of magnitude, often to sub-second time scales. My work has implications on several key areas of wireless networking: It removes systematic failures from wireless routing and serves as a source of information for a wide range of protocols including the protocols for network management and diagnostics.

In recent years the need for multimedia packet data services in wireless networks has grown rapidly. To overcome that need third generation (3G) mobile services have been proposed. The fast growing demands multimedia services in 3G services brought the need for higher capacity. As a result of this, the improvement on throughput, traffic serving performance has become necessary in 3G systems. Code division multiple access (CDMA) technique is one of the most important 3G wireless mobile techniques that has been defined. The scheduling mechanisms used in CDMA plays an important role on the efficiency of the system. The power, rate and capacity parameters are variable and dependent to each other in designing a scheduling mechanism. The schedulers for CDMA decide which user will use the frequency band at which time interval with what power and rate. In this thesis different type of algorithms used in time slotted CDMA are studied and a new algorithm which supports Quality of Service (QoS) is proposed. The performance analysis of this proposed algorithm is done via simulation in comparison to selected CDMA schedulers.

A paradigm shift from static spectrum allocation to dynamic spectrum access (DSA) is becoming a reality due to the recent advances in cognitive radio, wide band spectrum sensing, and network aware real--time spectrum access. It is believed that DSA will allow wireless service providers (WSPs) the opportunity to dynamically access spectrum bands as and when they need it. Moreover, due to the presence of multiple WSPs in a region, it is anticipated that dynamic service pricing would be offered that will allow the end-users to move from long-term service contracts to more flexible short-term service models. In this research, we develop a unified economic framework to analyze the trading system comprising two components: i) spectrum owner--WSPs interactions with regard to dynamic spectrum allocation, and ii) WSP--end-users interactions with regard to dynamic service pricing. For spectrum owner--WSPs interaction, we investigate various auction mechanisms for finding bidding strategies of WSPs and revenue generated by the spectrum owner. We show that sequential bidding provides better result than the concurrent bidding when WSPs are constrained to at most single unit allocation. On the other hand, when the bidders request for multiple units, (i.e., they are not restricted by allocation constraints) synchronous auction mechanism proves to be beneficial than asynchronous auctions. In this regard, we propose a winner determination sealed-bid knapsack auction mechanism that dynamically allocates spectrum to the WSPs based on their bids. As far as dynamic service pricing is concerned, we use game theory to capture the conflict of interest between WSPs and end--users, both of whom try to maximize their respective net utilities. We deviate from the traditional per--service static pricing towards a more dynamic model where the WSPs might change the price of a service almost on a session by session basis. Users, on the other hand, have the freedom to choose their WSP based on the price offered. It is found that in such a greedy and non-cooperative behavioral game model, it is in the best interest of the WSPs to adhere to a price threshold which is a consequence of a price (Nash) equilibrium. We conducted extensive simulation experiments, the results of which show that the proposed auction model entices WSPs to participate in the auction, makes optimal use of the common spectrum pool, and avoids collusion among WSPs. We also demonstrate how pricing can be used as an effective tool for providing incentives to the WSPs to upgrade their network resources and offer better services.

No description available.

The rapid growth of the Internet of Things (IoT) introduces an additional challenge to the existing spectrum under-utilisation problem as large scale deployments of thousands devices are expected to require wireless connectivity. Dynamic Spectrum Access (DSA) has been proposed as a means of improving the spectrum utilisation of wireless systems. Based on the Cognitive Radio (CR) paradigm, DSA enables unlicensed spectrum users to sense their spectral environment and adapt their operational parameters to opportunistically access any temporally unoccupied bands without causing interference to the primary spectrum users. In the same context, CR inspired Machine-to-Machine (M2M) communications have recently been proposed as a potential solution to the spectrum utilisation problem, which has been driven by the ever increasing number of interconnected devices. M2M communications introduce new challenges for CR in terms of operational environments and design requirements. With spectrum sensing being the key function for CR, this thesis investigates the performance of spectrum sensing and proposes novel sensing approaches and models to address the sensing problem for cognitive M2M deployments. In this thesis, the behaviour of Energy Detection (ED) spectrum sensing for cognitive M2M nodes is modelled using the two-wave with dffi use power fading model. This channel model can describe a variety of realistic fading conditions including worse than Rayleigh scenarios that are expected to occur within the operational environments of cognitive M2M communication systems. The results suggest that ED based spectrum sensing fails to meet the sensing requirements over worse than Rayleigh conditions and consequently requires the signal-to-noise ratio (SNR) to be increased by up to 137%. However, by employing appropriate diversity and node cooperation techniques, the sensing performance can be improved by up to 11.5dB in terms of the required SNR. These results are particularly useful in analysing the eff ects of severe fading in cognitive M2M systems and thus they can be used to design effi cient CR transceivers and to quantify the trade-o s between detection performance and energy e fficiency. A novel predictive spectrum sensing scheme that exploits historical data of past sensing events to predict channel occupancy is proposed and analysed. This approach allows CR terminals to sense only the channels that are predicted to be unoccupied rather than the whole band of interest. Based on this approach, a spectrum occupancy predictor is developed and experimentally validated. The proposed scheme achieves a prediction accuracy of up to 93% which in turn can lead to up to 84% reduction of the spectrum sensing cost. Furthermore, a novel probabilistic model for describing the channel availability in both the vertical and horizontal polarisations is developed. The proposed model is validated based on a measurement campaign for operational scenarios where CR terminals may change their polarisation during their operation. A Gaussian approximation is used to model the empirical channel availability data with more than 95% confi dence bounds. The proposed model can be used as a means of improving spectrum sensing performance by using statistical knowledge on the primary users occupancy pattern.

Wireless Underground Sensor Networks (WUSNs) are the networks of wireless sensors that operate below the ground surface. These sensors are either buried completely in soil medium, or placed within a bounded open underground space, such as underground mines and tunnels. WUSNs enable a wide variety of novel applications, including intelligent irrigation, underground structure monitoring, and border patrol and intruder detection. This thesis is concerned with establishing reliable and efficient communications in the network of wireless sensor nodes that are deployed in either soil medium or underground mines and tunnels. In particular, to realize WUSNs in soil medium, two types of signal propagation techniques including Electromagnetic (EM) waves and Magnetic Induction (MI) are explored. For EM wave-based WUSNs, the heterogeneous network architecture and dynamic connectivity are investigated based on a comprehensive channel model in soil medium. Then a spatio-temporal correlation-based data collection schemes is developed to reduce the sensor density while keeping high monitoring accuracy. For MI-based WUSNs, the MI channel is first analytically characterized. Then based on the MI channel model, the MI waveguide technique is developed in order to enlarge the underground transmission range. Finally, the optimal deployment algorithms for MI waveguides in WUSNs are analyzed to construct the WUSNs with high reliability and low costs. To realize WUSNs in underground mines and tunnels, a mode-based analytical channel model is first proposed to accurately characterize the signal propagation in both empty and obstructed mines and tunnels. Then the Multiple-Input and Multiple-Output (MIMO) system and cooperative communication system are optimized to establish reliable and efficient communications in underground mines and tunnels.