759 research outputs found

    An analysis on decentralized adaptive MAC protocols for Cognitive Radio networks

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    The scarcity of bandwidth in the radio spectrum has become more vital since the demand for more and more wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum and inefficiency in its utilization has been smartly addressed by the Cognitive Radio (CR) Technology which is an opportunistic network that senses the environment, observes the network changes, and then using knowledge gained from the prior interaction with the network, makes intelligent decisions by dynamically adapting their transmission characteristics. In this paper some of the decentralized adaptive MAC protocols for CR networks have been critically analyzed and a novel adaptive MAC protocol for CR networks, DNG-MAC which is decentralized and non-global in nature, has been proposed. The results show the DNG-MAC out performs other CR MAC protocols in terms of time and energy efficiency

    Greediness control algorithm for multimedia streaming in wireless local area networks

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    This work investigates the interaction between the application and transport layers while streaming multimedia in a residential Wireless Local Area Network (WLAN). Inconsistencies have been identified that can have a severe impact on the Quality of Experience (QoE) experienced by end users. This problem arises as a result of the streaming processes reliance on rate adaptation engines based on congestion avoidance mechanisms, that try to obtain as much bandwidth as possible from the limited network resources. These upper transport layer mechanisms have no knowledge of the media which they are carrying and as a result treat all traffic equally. This lack of knowledge of the media carried and the characteristics of the target devices results in fair bandwidth distribution at the transport layer but creates unfairness at the application layer. This unfairness mostly affects user perceived quality when streaming high quality multimedia. Essentially, bandwidth that is distributed fairly between competing video streams at the transport layer results in unfair application layer video quality distribution. Therefore, there is a need to allow application layer streaming solutions, tune the aggressiveness of transport layer congestion control mechanisms, in order to create application layer QoE fairness between competing media streams, by taking their device characteristics into account. This thesis proposes the Greediness Control Algorithm (GCA), an upper transport layer mechanism that eliminates quality inconsistencies caused by rate / congestion control mechanisms while streaming multimedia in wireless networks. GCA extends an existing solution (i.e. TCP Friendly Rate Control (TFRC)) by introducing two parameters that allow the streaming application to tune the aggressiveness of the rate estimation and as a result, introduce fair distribution of quality at the application layer. The thesis shows that this rate adaptation technique, combined with a scalable video format allows increased overall system QoE. Extensive simulation analysis demonstrate that this form of rate adaptation increases the overall user QoE achieved via a number of devices operating within the same home WLAN

    Service Differentiation Using p-Persistent CSMA/CA

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    The problem of service differentiation in wireless LANs is of utmost importance compared to wired networks. Multimedia communication via wireless LANs needs larger bandwidth compared to non-multimedia communications. Hence, a service differentiation scheme to enhance the distinction of service offered to different class priorities is essential. The objective of this thesis is to study the problem of providing service differentiation using proposed p-Persistent CSMA approach and the existing contention window scheme. The areas of this study include service differentiation schemes in p-Persistent CSMAs, various contention window schemes and a number of adaptive service differentiation schemes. Also, a service differentiation rule is used to distinguish the services offered to various classes of traffic.Computer Science Departmen

    Decentralised Learning MACs for Collision-free Access in WLANs

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    By combining the features of CSMA and TDMA, fully decentralised WLAN MAC schemes have recently been proposed that converge to collision-free schedules. In this paper we describe a MAC with optimal long-run throughput that is almost decentralised. We then design two \changed{schemes} that are practically realisable, decentralised approximations of this optimal scheme and operate with different amounts of sensing information. We achieve this by (1) introducing learning algorithms that can substantially speed up convergence to collision free operation; (2) developing a decentralised schedule length adaptation scheme that provides long-run fair (uniform) access to the medium while maintaining collision-free access for arbitrary numbers of stations

    VoIP Call Admission Control in WLANs in Presence of Elastic Traffic

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    VoIP service over WLAN networks is a promising alternative to provide mobile voice communications. However, several performance problems appear due to i) heavy protocol overheads, ii) unfairness and asymmetry between the uplink and downlink flows, and iii) the coexistence with other traffic flows. This paper addresses the performance of VoIP communications with simultaneous presence of bidirectional TCP traffic, and shows how the presence of elastic flows drastically reduces the capacity of the system. To solve this limitation a simple solution is proposed using an adaptive Admission and Rate Control algorithm which tunes the BEB (Binary Exponential Backoff) parameters. Analytical results are obtained by using an IEEE 802.11e user centric queuing model based on a bulk service M=G[1;B]=1=K queue, which is able to capture the main dynamics of the EDCA-based traffic differentiation parameters (AIFS, BEB and TXOP). The results show that the improvement achieved by our scheme on the overall VoIP performance is significant

    Smart PIN: performance and cost-oriented context-aware personal information network

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    The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches
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