Evaluation of Intelligent

This paper elaborates metrics for evaluation of agent based frameworks, exploited in semantic web. It is an extension of authors2019; earlier work in which different frameworks focusing on different issues of multi-agent system communication were proposed. This work while integrating all our earlier proposed frameworks aims to evaluate this integrated framework on existing metrics to explore its applicability in real world applications

A Novel Approach for Always Best Connected in Future Wireless Networks

Basically, Vertical handover (VHO) decision relies on the selection of the 2018;best2019; available network that could meet the QoS requirements for the end-user. Therefore, a network selection mechanism is required to help mobile users choose the best network; that is, one that provides always best connected (ABC) that suits users needs and is able to change dynamically with the change in conditions. The definition of best depends on a number of different aspects such as user personal preferences, device size and capabilities, application requirements, security, present network traffic, and network signal strength. This work proposes to assign weight to all the above stated aspects so as to compute ABC. The novelty of this work is to exploit intelligent agents for weight calculations after analyzing the explored parameters for various networks. An analysis and a comparison of both services and factors for different networks are also provided in the paper

Clustering in Aggregated User Profiles Across Multiple Social Networks

A social network is indeed an abstraction of related groups interacting amongst themselves to develop relationships. However, toanalyze any relationships and psychology behind it, clustering plays a vital role. Clustering enhances the predictability and discoveryof like mindedness amongst users. This article’s goal exploits the technique of Ensemble K-means clusters to extract the entities and their corresponding interestsas per the skills and location by aggregating user profiles across the multiple online social networks. The proposed ensemble clustering utilizes known K-means algorithm to improve results for the aggregated user profiles across multiple social networks. The approach produces an ensemble similarity measure and provides 70% better results than taking a fixed value of K or guessing a value of K while not altering the clustering method. This paper states that good ensembles clusters can be spawned to envisage the discoverability of a user for a particular interest

A novel agent based autonomous and service composition framework for cost optimization of resource provisioning in cloud computing

A cloud computing environment offers a simplified, centralized platform or resources for use when needed at a low cost. One of the key functionalities of this type of computing is to allocate the resources on an individual demand. However, with the expanding requirements of cloud user, the need of efficient resource allocation is also emerging. The main role of service provider is to effectively distribute and share the resources which otherwise would result into resource wastage. In addition to the user getting the appropriate service according to request, the cost of respective resource is also optimized. In order to surmount the mentioned shortcomings and perform optimized resource allocation, this research proposes a new Agent based Automated Service Composition (A2SC) algorithm comprising of request processing and automated service composition phases and is not only responsible for searching comprehensive services but also considers reducing the cost of virtual machines which are consumed by on-demand services only