Faculty of Computing

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4202

Browse

Filters

2014 - 20194

Advanced Search

Filter by

Settings

Subject: search.filters.subject.performance

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    PublicationEmbargo
    Analysis and performance of CMA blind deconvolution for image restoration
    (Wiley Online Library, 2015-09) Samarasinghe, P; Kennedy, R. A
    In this paper we study the applicability of classical blind deconvolution methods such as constant modulus algorithm (CMA) for blind adaptive image restoration. The requirements such as the source to be white, uniformly distributed and zero mean, which yield satisfactory convergence in the data communication application context, are revisited in the image restoration context, where a linear deblur kernel needs to be blindly adapted to compensate for an unknown image blur kernel with the objective to recover a source ground truth image. Through analysis and performance studies, we show that the performance of CMA is adversely affected by the intrinsic spatial correlation of natural images and by any deviation of their distribution from being platykurtic. We also show that decorrelation techniques designed to overcome spatial correlation cannot be effectively applied to rectify CMA performance for blind adaptive image restoration
  • Thumbnail Image
    PublicationEmbargo
    The performance of page rank algorithm under degree preserving perturbations
    (IEEE, 2014-12-09) Senanayake, U; Szot, P; Piraveenan, M; Kasthurirathna, D
    Page rank is a ranking algorithm based on a random surfer model which is used in Google search engine and many other domains. Because of its initial success in Google search engine, page rank has become the de-facto choice when it comes to ranking nodes in a network structure. Despite the ubiquitous utility of the algorithm, little is known about the effect of topology on the performance of the page rank algorithm. Hence this paper discusses the performance of page rank algorithm under different topological conditions. We use scale-free networks and random networks along with a custom search engine we implemented in order to experimentally prove that the performance of page rank algorithm is deteriorated when the random network is perturbed. In contrast, scale-free topology is proven to be resilient against degree preserving perturbations which aids the page rank algorithm to deliver consistent results across multiple networks that are perturbed to varying proportions. Not only does the top ranking results emerge as stable nodes, but the overall performance of the algorithm is proven to be remarkably resilient which deepens our understanding about the risks in applying page rank algorithm without an initial analysis on the underlying network structure. The results conclusively suggests that while page rank algorithm can be applied to scale-free networks with relatively low risk, applying page rank algorithm to other topologies can be risky as well as misleading. Therefore, the success of the page rank algorithm in real world in search engines such as Google is at least partly due to the fact that the world wide web is a scale-free network. Since the world wide web is constantly evolving, we postulate that if the topological structure of the world wide web changes significantly so that it loses its scale-free nature to some extent, the page rank algorithm will not be as effective.
  • Thumbnail Image
    PublicationEmbargo
    Operational Performance and Security Improvement Approach for Integrated BigData and Industrial IoT in Cyber-Physical Communication Systems
    (IEEE, 2019-05-09) Jayawardena, C; Sen, S
    Well-performed secure computing and communication are at the forefront for Internet of Things (IoT) and Cyber-Physical Systems (CPS). By using these innovative technologies, Industrial-IoT (IIoT) has revolutionized the smart industrial processes while this evolution imposes mandatory requirements of reliable, cybersecure and well performed network. This implants adopting effective approaches of improving performance and cybersecurity in IIoT networks towards building a trusted cyber-physical communication. IIoT generates huge data of which some are real-time and rest are big data which needs assurance of delivery without loss. This report has modeled the performance and security issues of intelligent physical systems. While demonstrating the performance and security strategies of improving them, this paper addresses issues for consideration to overcome the security and performance improvement bottlenecks.
  • Thumbnail Image
    PublicationEmbargo
    Analysis of network techniques and cybersecurity for improving performance of big data IoT and cyber-physical communication internetwork
    (IEEE, 2019-02-13) Sen, S; Jayawardena, C
    The Internet of Things (IoT) and Cyber-Physical Systems (CPS), are generating wide spread data. The success of these trio depends on a well performed cyber-communication infrastructure. This necessitates improving the performance of the cyber-communication internetwork; this performance improvement includes optimization of network techniques as well as the security of the cyber-network. Internet infrastructure has been upgraded to higher level ever than before, where we are enjoying technologies like fibre, 10-gig ethernet and even 100-gig ethernet, but there is no guarantee of communication in the cyber space, internet still providing packet delivery on "best effort" basis. On the other side, cyber hackers are targeting big physical infrastructures, industrial hardware in addition to the financial institutions. Therefore, it has become vital to address secure and faster data communications, in order to improve the Performance of the Internetwork.