M Tech Dissertations

Permanent URI for this collectionhttp://ir.daiict.ac.in/handle/123456789/3

Browse

Subject: search.filters.subject.Management

Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    ItemOpen Access
    Traffic profile measurement and traffic driven network reconfiguration
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2011) Monga, Jasneet Kaur; Srivastava, Sanjay
    In multi hop ad hoc network, nodes are constrained by the power or the energy sources that are available. Efficient algorithms for saving the energy are required to manage the network in such a manner that the resources available, get properly utilized and nodes in the network do not drain out. Switching and working over idle and busy periods of a node, one can achieve this dual goal and it comes under the category of sleep scheduling. In this approach, the basic emphasis is on the traffic profiles of the network nodes which is estimated based on the network traffic flows. The traffic estimated becomes the weight of the path between the different source destination pairs available in the network and this value averaged either at the local level or the global level is needed to be reduced, hence saving the overall energy of the network. The traffic weighted paths which consume energy above the average or the threshold value become the prime candidates for the consideration. The aim is to go for shorter and lighter paths in the network which require the sleeping nodes in the proximity of heavy and longer paths to be awaken to be a part of network topology and saving the extra energy wasted on longer paths. This makes the nodes in longer paths go through a sleep state so that they can be utilized when they are required, hence making topology changes by reconfiguring the paths.
  • Thumbnail Image
    ItemOpen Access
    Resource allocation on infrastructure as a service cloud using policies
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2010) Nathani, Amit; Divakaran, Srikrishnan
    Conventionally, a cloud refers to an Infrastructure as a service cloud. Infrastructure as a service cloud providers manage a large set of computing resources. These resources can be provided to cloud users on demand in the form of virtual machines. Cloud consumers do not need to manage resources and be worried about the performance issues because they are handled by cloud providers. Resource allocation in the context of infrastructure as a service cloud means allocating virtual resources namely computing capacity, storage etc. to competing requests based on pre-defined resource allocation policies. In real world most of the Infrastructure as a service clouds rely on simple resource allocation policies like immediate and best effort. Immediate means the resources are allocated if they are available or the request is rejected and best effort means the requested resources are allocated if they are available or the request is placed in first come first serve queue. Sometimes it is not possible for a cloud provider to satisfy all the requests which come to them immediately because of lack of resources. In this case cloud providers can benefit from more complex resource allocation policies. Haizea is a resource lease manager that tries to address above issues. It uses resource leases as resource allocation abstraction and implements these leases as virtual machines. Currently, it supports four kinds of resource allocation policies: immediate, best-effort, advance reservation and deadline sensitive. The aim of thesis is to extend the current scheduling algorithm of Haizea to support deadline leases in an efficient manner. A dynamic planning based scheduling algorithm is proposed which will admit new leases and prepare the schedule whenever a new lease can be accommodated. The proposed algorithm is implemented in Haizea. Experiments are performed to demonstrate the effectiveness of it. The results show that it maximizes resource utilization and acceptance of leases compared to the existing algorithm of Haizea.
  • Thumbnail Image
    ItemOpen Access
    Negotiation for resource allocation on infrastructure as a service cloud
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2010) Akhani, Janki; Divakaran, Srikrishnan
    The Cloud is a computing platform that provides dynamic resource pools, virtualization, and high availability. Cloud computing infrastructures can allow enterprises to achieve more efficient use of their IT hardware and software investments. Infrastructure As A Service (IAAS) cloud providers manage a large set of computing resources. These resources can be provided to cloud consumers on demand in the form of virtual machines. Cloud consumers do not need to manage resources and be worried about the performance issues because they are handled by cloud providers. Open Nebula is an open source cloud toolkit which can be used to setup an IAAS cloud. It has three components: Open Nebula Core, Virtual Machine Scheduler and Cloud Drivers. Haizea is an open-source resource lease manager, and can act as a virtual machine scheduler for Open Nebula or used on its own as a simulator to evaluate the performance of different scheduling strategies. Haizea supports four kinds of resource allocation policies: immediate, best-effort, advance reservation and deadline sensitive. To reserve resources in advance using Haizea, consumer submits parameters like amount of resources, start time and duration of a reservation as a request. If one or more parameters can not be satisfied, then Haizea will reject the request. This method is very rigid method because it does not allow negotiation of any parameter. Consumer can resubmit new requests by modifying previously submitted request parameters. Consumer will not be aware of the current resource allocation on provider side so, the chances of new requests getting rejected are more. Thus, it will increase communication overhead between cloud provider and consumer as well as it will decrease resource utilization on provider’s side. It will also degrade the performance of a provider in managing many incoming requests due to previously rejected ones. To overcome the above problems, negotiation can be provided. Negotiation process consists of three components which are negotiation protocol, negotiation objectives and agents’ decision making algorithm. The proposed algorithm to generate set of counter offers is a part of decision making model at provider side. It provides set of counter offers to consumer when his advance reservation request gets rejected. It provides set of counter offers considering parameters’ flexibilities to maximize the chances of their acceptance. The proposed algorithm for User selection policy is a part of decision making model at consumer side. Consumer can get best suitable offer from set of counter offers using the algorithm of user selection policy. Ranking algorithm is a partof algorithm for user selection policy. Using this ranking algorithm, consumers will get suitable offers sorted according to their needs. It will reduce consumers’ efforts to go through all the provided counter offers and choose best suitable one. These algorithms are implemented in Haizea. Experiments are performed to demonstrate the effectiveness of algorithms. The results show that the proposed algorithm to generate counter offers maximizes resource utilization and acceptance of requests compared to rigid and exact methods.
  • Thumbnail Image
    ItemOpen Access
    FPGA implementation of direct sequence spread spectrum techniques
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2008) Choudhary, Vivek Kumar; Dubey, Rahul
    This work presents the performance, noise analysis and FPGA implementation of Direct Sequence Spread Spectrum technique. Performance of signal increases as increasing parity bits in Hamming code algorithm. Increasing parity noise goes reduce therefore received signal close to its original value, but adding parity band-width requirement also increases. This work is bases on the IS-95 standard for CDMA (Code Division Multiple Access) Digital Cellular.
  • Thumbnail Image
    ItemOpen Access
    Packet scheduling algorithm to improve delay bounds in HSDPA
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2007) Pradhan, Pratik; Jotwani, Naresh D.
    With tremendous growth in mobile subscribers in recent past and trend of accessing packet data services in wireless networks, 3GPP has introduced an enhancement to Universal Mobile Telecommunications System (UMTS) standard known as High Speed Downlink Packet Access (HSDPA) to provide high data rate services, especially in the downlink. The main focus of HSDPA concept is to increase peak data rates, improve Quality of Service (QoS) and enhance the spectral efficiency for downlink packet data traffic. HSDPA introduces new transport channel named High Speed-Downlink Shared Channel (HS-DSCH) in downlink that is shared among the users accessing packet data services. Scheduling of these users is one of the most challenging and interesting problem because of constantly varying state of the wireless channel. The problem is even worse when users require certain level of QoS and the transmission rate supported by wireless channel is also varying. The Exponential Scheduling Algorithm, proposed in literature, is a good candidate to provide bounded delays when QoS requirements are speci¯ed in terms of maximum tolerable delays, but the investigations in this thesis show that it fails to provide delay bounds when it is still possible with some trade-o® with system throughput and sometimes not even that. The thesis proposes Delay Sense-Exponential Scheduling Algorithm, a variant of Exponential Scheduling Algorithm, to improve on the delay bounds provided by Exponential algorithm. The simulation results ensure that the new proposed algorithm improves on providing delay bounds to the Real Time (RT) services simultaneously providing comparable throughput to Non-Real Time (NRT) services. The proposed algorithm is studied under wide range of scenarios including NRT, RT and mixture of NRT and RT services.