424 research outputs found

    DIRECTIONAL ANTENNA BASED EFFICIENT LOCATION AWARE ROUTING IN MOBILE ADHOC NETWORK

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    Mobile Adhoc Network (MANET) also called as wireless ad hoc network is a self-organizing, self-configuring infrastructure less network containing a group of mobile nodes communicating wirelessly. As the hosts move often resulting in dynamic topology of the network, routing seeks more attention. Therefore, routing protocol using node’s location information like LAR (location aided routing) has emerged as potential solution. Here, the route discovery is limited to a small region named as request zone in contrast to blind flooding over the entire network. Also it is noticeable that the shape and size of the request zone play a vital role in enhancing the protocol’s performance. After various analyses it was concluded that for higher node density, elliptical shaped request zone performs better than other possible shapes. Further, suitable route must be chosen based on current load status of the network so that successful delivery of packets is ensured. Generally, omni-directional antennas are used for communication between moving motes. The disadvantage of mobile ad hoc networks with omni-directional antenna lies in the limited capacity caused by high interference and low spatial reuse. This paper focuses on obtaining optimal size for request zone in accordance with varying node density. Further, optimal path between source and destination is selected using Dijkstra’s algorithm. Our simulation results show that directional antennas outshines the performance of omni-directional antennas in increasing transmission range of nodes, reducing the number of redundant nodes involving in data communication etc

    Enabling reliable and power efficient real-time multimedia delivery over wireless sensor networks

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    There is an increasing need to run real-time multimedia applications, e.g. battle field and border surveillance, over Wireless Sensor Networks (WSNs). In WSNs, packet delivery exhibits high packet loss rate due to congestion, wireless channel high bit error rate, route failure, signal attenuation, etc... Flooding conventional packets over all sensors redundantly provides reliable delivery. However, flooding real-time multimedia packets is energy inefficient for power limited sensors and causes severe contentions affecting reliable delivery. We propose the Flooding Zone Initialization Protocol (FZIP) to enhance reliability and reduce power consumption of real-time multimedia flooding in WSNs. FZIP is a setup protocol which constrains flooding within a small subset of intermediate nodes called Flooding Zone (FZ). Also, we propose the Flooding Zone Control Protocol (FZCP) which monitors the session quality and dynamically changes the FZ size to adapt to current network state, thus providing a tradeoff of good quality and less power consumption

    Workload Prediction for Efficient Performance Isolation and System Reliability

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    In large-scaled and distributed systems, like multi-tier storage systems and cloud data centers, resource sharing among workloads brings multiple benefits while introducing many performance challenges. The key to effective workload multiplexing is accurate workload prediction. This thesis focuses on how to capture the salient characteristics of the real-world workloads to develop workload prediction methods and to drive scheduling and resource allocation policies, in order to achieve efficient and in-time resource isolation among applications. For a multi-tier storage system, high-priority user work is often multiplexed with low-priority background work. This brings the challenge of how to strike a balance between maintaining the user performance and maximizing the amount of finished background work. In this thesis, we propose two resource isolation policies based on different workload prediction methods: one is a Markovian model-based and the other is a neural networks-based. These policies aim at, via workload prediction, discovering the opportune time to schedule background work with minimum impact on user performance. Trace-driven simulations verify the efficiency of the two pro- posed resource isolation policies. The Markovian model-based policy successfully schedules the background work at the appropriate periods with small impact on the user performance. The neural networks-based policy adaptively schedules user and background work, resulting in meeting both performance requirements consistently. This thesis also proposes an accurate while efficient neural networks-based pre- diction method for data center usage series, called PRACTISE. Different from the traditional neural networks for time series prediction, PRACTISE selects the most informative features from the past observations of the time series itself. Testing on a large set of usage series in production data centers illustrates the accuracy (e.g., prediction error) and efficiency (e.g., time cost) of PRACTISE. The superiority of the usage prediction also allows a proactive resource management in the highly virtualized cloud data centers. In this thesis, we analyze on the performance tickets in the cloud data centers, and propose an active sizing algorithm, named ATM, that predicts the usage workloads and re-allocates capacity to work- loads to avoid VM performance tickets. Moreover, driven by cheap prediction of usage tails, we also present TailGuard in this thesis, which dynamically clones VMs among co-located boxes, in order to efficiently reduce the performance violations of physical boxes in cloud data centers

    Improving the Utilization of an Elastic Resource: A Client-side Approach

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    Resource management is traditionally addressed by policies implemented inside the resource provider. Here we study the problem with an attitude that is specular but complementary, which consists in designing a distributed client-side access regulation algorithm that improves the utilization of an elastic resource. The introduction of elastic resources — a feature of the cloud computing paradigm — complicates their management since, when the workload applied on the resource varies (for instance with the number of users) the resource automatically follows such variations with its capacity. But the presence of an extra computational cost related with capacity variations motivates a non linear, lazy response, that penalizes dynamic environments. Hence the interest for an algorithm that shapes the production of service requests on the client side. To make our investigation more adherent to a practical environment, we introduce a real time requirement: each client must have access to the service at least every π time units. Examples of this requirement, that features a bounded degree of asynchrony, are found, for instance, in network streaming applications: stream chunks must feed the input buffer at the destination. The algorithm we investigate is based on the random walk of a token. To evaluate the range of applicability of the algorithm, we define an analytic model of its stochastic behavior — described by a non-Markov process — and then we compare its performance with a benchmark algorithm, representative of an effective solution that is often used in practice

    Development of wireless control and automation systems

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    Ph.DDOCTOR OF PHILOSOPH

    Using Reputation Based Trust to Overcome Malfunctions and Malicious Failures in Electric Power Protection Systems

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    This dissertation advocates the use of reputation-based trust in conjunction with a trust management framework based on network flow techniques to form a trust management toolkit (TMT) for the defense of future Smart Grid enabled electric power grid from both malicious and non-malicious malfunctions. Increases in energy demand have prompted the implementation of Smart Grid technologies within the power grid. Smart Grid technologies enable Internet based communication capabilities within the power grid, but also increase the grid\u27s vulnerability to cyber attacks. The benefits of TMT augmented electric power protection systems include: improved response times, added resilience to malicious and non-malicious malfunctions, and increased reliability due to the successful mitigation of detected faults. In one simulated test case, there was a 99% improvement in fault mitigation response time. Additional simulations demonstrated the TMT\u27s ability to determine which nodes were compromised and to work around the faulty devices when responding to transient instabilities. This added resilience prevents outages and minimizes equipment damage from network based attacks, which also improves system\u27s reliability. The benefits of the TMT have been demonstrated using computer simulations of dynamic power systems in the context of backup protection systems and special protection systems

    Implementation and Evaluation of A Low-Cost Intrusion Detection System For Community Wireless Mesh Networks

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    Rural Community Wireless Mesh Networks (WMN) can be great assets to rural communities, helping them connect to the rest of their region and beyond. However, they can be a liability in terms of security. Due to the ad-hoc nature of a WMN, and the wide variety of applications and systems that can be found in such a heterogeneous environment there are multiple points of intrusion for an attacker. An unsecured WMN can lead to privacy and legal problems for the users of the network. Due to the resource constrained environment, traditional Intrusion Detection Systems (IDS) have not been as successful in defending these wireless network environments, as they were in wired network deployments. This thesis proposes that an IDS made up of low cost, low power devices can be an acceptable base for a Wireless Mesh Network Intrusion Detection System. Because of the device's low power, cost and ease of use, such a device could be easily deployed and maintained in a rural setting such as a Community WMN. The proposed system was compared to a standard IDS solution that would not cover the entire network, but had much more computing power but also a higher capital cost as well as maintenance costs. By comparing the low cost low power IDS to a standard deployment of an open source IDS, based on network coverage and deployment costs, a determination can be made that a low power solution can be feasible in a rural deployment of a WMN

    A computer vision-based proposal for seat occupancy monitoring applied to FEUP's library

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    FEUP students frequently find themselves without a proper seating area when seeking the library for their studying efforts. Furthermore, this situation tends to be exacerbated during evaluation periods. As an attempt to minimize this issue, the work for this dissertation will aim to develop a vision-based system, which will allow students and staff: -- to know, in real-time, which seating areas are available or occupied. -- consult an accessible dashboard, containing a complete history, seat mapping, and other relevant statistical data. The solution is two-tiered, the first one dealing with the direct detection of seated people. Though this information could be retrieved through the check-in and -out system already put in place, several instances remain where the students cannot be expected to cooperate fully, creating gaps in the data. For this purpose, there is a need for a low-cost technology (i.e. there are many seating options spread out), which is also non-invasive (i.e. little to no cabling) and of easy maintenance (i.e. low-powered, simple installation). There is a great range of possible methods available for this particular problem, such as a small, dedicated module per seat or table (i.e. microcontroller, IR-sensor, and a wireless communication system). The choice, however, fell upon a vision-based system, which will be able to cover all relevant areas and remain open to changes in layout and detection options. The second tier of the system includes a Web interface, accessible to everyone involved with FEUP, including all relevant information for the everyday activities and management of the building, as previously mentioned. Although many options already exist in the current market and could replicate these very same features (examples: https://tinyurl.com/y23gdt4d, https://floorsen.se/), there are two common disadvantages: a high cost and difficulty of integration with other existing systems, as they are closed and rely on proprietary technology. In this landscape, an opportunity arises to develop a system with truly differentiating characteristics. The work will be done in cooperation with the Serviços da Biblioteca da FEUP
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