Nick Antonopoulos

CinemaScreen recommender agent: combining collaborative and content-based filtering

A film recommender agent expands and fine-tunes collaborative-filtering results according to filtered content elements - namely, actors, directors, and genres. This approach supports recommendations for newly released, previously unrated titles. Directing users to relevant content is increasingly important in todays society with its ever-growing information mass. To this end, recommender systems have become a significant component of e-commerce systems and an interesting application domain for intelligent agent technology.

Investigation of IT Security and Compliance Challenges in Security-as-a-Service for Cloud Computing

The key security challenges and solutions on the cloud have been investigated in this paper with the help of literature reviews and an experimental model created on OPNET that is simulated to produce useful statistics to establish the approach that the cloud computing service providers should take to provide optimal security and compliance. The literatures recommend the concept of Security-as-a-Service using unified threat management (UTM) for ensuring secured services on the cloud. Through the simulation results, this paper has demonstrated that UTM may not be a feasible approach to security implementation as it may become a bottleneck for the application clouds. The fundamental benefits of cloud computing (resources on demand and high elasticity) may be diluted if UTMs do not scale up effectively as per the traffic loads on the application clouds. Moreover, it is not feasible for application clouds to absorb the performance degradation for security and compliance because UTM will not be a total solution for security and compliance. Applications also share the vulnerabilities just like the systems, which will be out of UTM clouds control.

Social Peer-to-Peer for Resource Discovery

For resource discovery in social networks, people can directly contact some acquaintances that have knowledge about the resources they are looking for. However, in current peer-to-peer networks, peer nodes lack capabilities similar to social networks, making it difficult to route queries efficiently. In this paper, we present a social-like system (Social-P2P) for resource discovery by mimicking human behaviours in social networks. Different from most informed search algorithms, peer nodes learn knowledge from the results of previous searches and no additional overhead is required to obtain extra information from neighbouring nodes. Unlike community-based P2P information sharing systems, we do not intend to create and maintain peer groups or communities consciously. Peer nodes with the same interests will be highly connected to each other spontaneously. Social-P2P has been simulated in a dynamic environment. From the simulation results and analysis, Social-P2P achieved better performance than current methods

The Inter-cloud Meta-scheduling (ICMS) Framework

This work covers the inter-cloud meta-scheduling system that encompasses the essential components of the interoperable cloud setting for wide service dissemination. The study herein illustrates a set of distributed and decentralized operations by highlighting meta-computing characteristics. This is achieved by using meta-brokers that determine a middle-standing component for orchestrating the decision making process in order to select the most appropriate datacenter resource among collaborated clouds. The selection is based on heuristic performance criteria (e.g. the service execution time, latency, energy efficiency etc.). Our solution is more advanced when compared to conventional centralized schemes, as it offers robust real-time scalable, elastic and flexible service scheduling in a fully decentralized and dynamic manner. Similarly, issues related with bottleneck on multiple service requests, heterogeneity, information exposition and consideration of variation of workloads are of prime focus. In view of that, the whole process is based upon random service requests from users that are clients of a sub-cloud of an inter-cloud datacenter and access is done via a meta-broker. The inter-cloud facility distributes the request for service by enclosing each personalized service into a host virtual machine. The study presents a detailed discussion of the algorithmic model for demonstrating the whole service dissemination, allocation, execution and monitoring process along with the preliminary implementation and configuration on a proposed SimIC simulation framework.

An optimized two-tier P2P architecture for contextualized keyword searches

We describe a two-tiered P2P network for efficient lookup of contextualized data, utilizing an alternative strategy for building the network overlay designed to reduce the hops required to route lookups and improve fault tolerance by allowing the selection of nodes to build subrings. We show how the method is used to support context-keyword queries. Our calculations indicate that the technique yields improvements in the average query hop count while reducing the amount of state stored on each node. The use of Preference Lists can further reduce the average hop count through bypassing previously traversed segments of the structures

Load-driven neighbourhood reconfiguration of Gnutella overlay

Unstructured P2P networks support distributed applications whose workload may vary significantly over time and between nodes. Self-optimizing systems try to keep the load in the network balanced despite the frequent load fluctuations. Several P2P systems exhibit a number of related features but fail to avoid centralisation under high-load situations. ERGO aims to balance the overloaded nodes by rewiring some of their incoming links to underloaded ones via a set of interconnected servers which index the underloaded nodes. In two simulated environments, ERGO load-balancing on Gnutella network increases the balanced nodes and network availability by preserving its efficiency and even reducing its messages.

Military tactics in agent-based sinkhole attack detection for wireless ad hoc networks

Wireless Ad hoc Networks (WAHNs) offer a challenging environment for conventional Intrusion Detection Systems (IDSs). In particular WAHN have a dynamic topology, intermittent connectivity, resource constrained device nodes and possibly high node churn. Researchers over the past years have encouraged the use of agent-based IDS to overcome these challenges. In this work we propose the use of military tactics to optimise the operations of agent-based IDS for WAHN. We design an agent framework modeled over a military command structure and an agent behavioural model, which employs adapted military tactics to police routes, and detect intruders in the network. The tactical agents follow a risk-based approach such that the frequency of patrols is directly proportional to the risk factor of the route. Consequently, resources are conserved without impacting the effectiveness of the IDS. We demonstrate the proof of concept through a case study. In this study, we implement a simulation-based model of our solution to detect and recover from a Sinkhole attack in a Wireless Sensor Network (WSN), using the Ad hoc On Demand Distance Vector (AODV) as routing protocol. We evaluate the proof of concept in terms of the detection precision, data loss incurred from the attack and the agent overheads due to mobility and communication.

Efficient resource discovery in grids and P2P networks

Presents a new model for resource discovery in grids and peer‐to‐peer networks designed to utilise efficiently small numbers of messages for query processing and building of the network. Outlines and evaluates the model through a theoretical comparison with other resource discovery systems and a mathematical analysis of the number of messages utilised in contrast with Chord, a distributed hash table. Shows that through careful setting of parameter values the model is able to provide responses to queries and node addition in fewer messages than Chord. The model is shown to have significant benefits over other peer‐to‐peer networks reviewed. Uses a case study to show the applicability of the model as a methodology for building resource discovery systems in peer‐to‐peer networks using different underlying structures. Shows a promising new method of creating a resource discovery system by building a timeline structure on demand, which will be of interest to both researchers and system implementers in the fields of grid computing, peer‐to‐peer networks and distributed resource discovery in general.

Cloud Virtual Machine Scheduling: Modelling the Cloud Virtual Machine Instantiation

Cloud computing provides an efficient and flexible means for various services to meet the diverse and escalating needs of IT end-users. It offers novel functionalities including the utilization of remote services in addition to the virtualization technology. The latter feature offers an efficient method to harness the cloud power by fragmenting a cloud physical host in small manageable virtual portions. As a norm, the virtualized parts are generated by the cloud provider administrator through the hyper visor software based on a generic need for various services. However, several obstacles arise from this generalized and static approach. In this paper, we study and propose a model for instantiating dynamically virtual machines in relation to the current job characteristics. Following, we simulate a virtualized cloud environment in order to evaluate the models dynamic-ness by measuring the correlation of virtual machines to hosts for certain job variations. This will allow us to compute the expected average execution time of various virtual machines instantiations per job length.

Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies, and Applications

The Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies, and Applications addresses the need for peer-to-peer computing and grid paradigms in delivering efficient service-oriented computing. This critical mass of the most sought after research serves as a collection of chapters facilitating a broad understanding of the subject matter useful to researchers and doctoral students working specifically in the deployment, implementation, and study of related topics including distributed computing, software engineering, Web services, and modeling of business processes.