Queueing Network Models (QNMs) constitute robust quantitative tools for evaluating and predicting the Quality of Service (QoS) of virtual machine (VM) provisioning in Cloud Computing Platforms (CCPs). An extended application-driven open QNM at equilibrium with random routing and a First-Come-First-Served (FCFS) rule is proposed for the performance modelling and analysis of Infrastructure as a Service (IaaS) CCP architecture. It is assumed that the QNM has a bursty external arrival process of clients requesting VMs according to a Compound Poisson Process (CPP) with geometrically distributed batches, or equivalently, highly variable Generalised Exponential (GE) interarrival times. Moreover, it consists of L ( L ≥ 1 ) queueing stations with infinite buffer capacity and c i ( c i ≥ 1, i = 1, 2, …, L ) GE-type servers. By means of a generic maximum entropy (ME) product form approximation, the proposed QNM is decomposed into individual GE/GE/c i , i = 1, 2, …, L queueing stations with GE-type interarrival and service times, each of which can be analysed in isolation. Consequently, closed-form expressions for key performance metrics of each queueing station i, i = 1, 2, …, L of the GE-type QNM are devised, such as those of throughput, server (resource) utilisation, mean response time and steady state probability of number of VM requests by clients. Moreover, typical numerical experiments are carried out, based on exponential memoryless (M−type), a family of two-phase Hyperexponential-2 (H 2 ), and GE interarrival and service time distributions of the QNM, using MATLAB and JMT tools as appropriate, which shows GE-type yield pessimistic bound or worst-case performance. The evaluation of the performance metrics of the QNM and the prediction of related bottlenecks were presented. This will provide vital insights for capacity planning at the design and development stage of new IaaS CCP architectures, as well as for tuning and upgrading existing ones to facilitate effective processing and leasing of VMs to requesting clients. We integrate our QNM into an expert system workflow comprising analytical outputs (such as overall delay W̄, station(s) utilisations ρ i , bottleneck identity) feed simple, auditable rules that recommend scale out, throttling, or routing adjustments. Sensitivity results are translated into proactive policies with clear thresholds.

SUMMARY Social networks have recently been gaining popularity. In a peer‐to‐peer mobile social network (MSN), users with similar interests establish groups or communities and share information without relying on a centralized infrastructure. Users socially interact with each other using handheld mobile devices and membership in a group/community of MSNs is granted by a pre‐existing group member. However, it is possible that a group of malicious users can collude to promote another untrustworthy user in becoming a group member. Moreover, revoking membership without the existence of a central authority in a group is also a grant challenge. To address these problems in peer‐to‐peer MSNs, we propose a decentralized framework and the related algorithms for trusted information exchange and social interaction among users based on the dynamicity aware graph relabeling system. In contrast to the existing implementations of social networks based on a client/server paradigm, the proposed framework utilizes a lightweight trust model for identifying trustworthy users and aims at creating communities of trusted users while isolating and reducing interactions with untrustworthy users. Simulation results demonstrated the effectiveness of the proposed framework compared with the traditional dynamicity aware graph relabeling system algorithm.Copyright © 2011 John Wiley & Sons, Ltd.

The rapid growth of emerging techniques for mobile resource sharing, content sharing, mobile social networks, and complex cyber-physical systems poses significant challenges for trust and security management. Several trust management schemes have been proposed recently to counter the security threat on Peer-to-Peer (P2P) systems. However, due to the difficulties caused by system mobility, wireless communications, pervasive devices and dynamic network topology, there is an increasing requirement of decentralized and distributed trust management schemes. In this paper, we first investigate and analyze various existing decentralized and distributed trust management schemes. Based on the analytical results, an efficient, accurate, robust and scalable light weight trust ratings aggregation scheme, referred to as M-trust, is proposed for mobile P2P networks. Extensive simulation results show that this proposed scheme can decrease the time required to compute the list of trust ratings and reduce the required storage space. The comparison to other schemes demonstrates that M-trust possesses the excellent overall performance in terms of accuracy, reliability, convergence speed, and detection rate under various constraints of mobility, trust threshold and network out-degree.

Cognitive Radio Networks (CRNs) are emerging as a viable solution for exploiting the available spectrum and solving overcrowding in the operating bands. Several dimensions in the process of identification, management and routing need to be handled to overcome the challenges associated with the management of CRNs. A very important topic in achieving an effective and flexible management solution is related to the data representation of the different CRN dimensions. Scalability, high tolerance to churn and low latencies in accessing the stored data are fundamental characteristics in order to keep up with the dynamic nature of a mobile environment. Accordingly, to achieve a robust data representation that can handle all these requirements in an efficient way we focus our attention on peer-to-peer (P2P) systems. These systems are well known for providing an efficient platform to develop scalable and robust applications. Hence, in this paper we investigate using geometric multi-dimensional data representation and addressing system based on basic CAN functionality. Results obtained in our experiments are reported, providing useful information to improve the resilience to churn of our system.

In Mobile Social Networks (MSN) users can participate in communication based on their mutual interests. Many solutions for Mobile Ad Hoc networks have been proposed however content based communication in partially or intermittently connected MANETs has been a recent research area. In this paper we p

Quality of service (QoS) provision will be one of the most challenging issues in the future heterogeneous wireless networks. It is also anticipated that new services will emerge, mainly for real-time and multimedia applications, which will need high data rates. One of the main aims of the future heterogeneous wireless networks is to allow mobile users to roam between different wireless networks operators and geographical areas while providing interactive broadband multimedia services and seamless connectivity. This paper focuses on the performance anaylsis of 4G network architecture where roaming connections are handled in an effective manner. The analysis is based on generalised buffer sharing, as a cost-effective resource sharing protocol, in support of multiple voice calls, streaming media and data packet service classes.

Summary form only given. The efficiency of a large-scale multicomputer is critically dependent on the performance of its underlying interconnection network. Dimension-ordered routing has been employed to transmit messages in multicomputer networks, as it requires a simple deadlock-avoidance algorithm, resulting in an efficient router implementation. The performance of this routing algorithm has been widely analysed under the assumption of the traditional Poisson arrival process, which is inherently unable to model traffic self-similarity revealed by many real-world applications. In an effort towards providing cost-effective tools that help investigating network performance under more realistic traffic loads, we propose an analytical model for dimension-ordered routing in k-ary n-cube networks when subjected to self-similar traffic. As the service time, blocking probability and waiting time experienced by a message vary from a dimension to another with dimension-ordered routing, the design of this model poses greater challenges. The model validity is demonstrated by performance results obtained from simulation experiments.

Abstract A novel one‐to‐all broadcasting scheme is proposed for arbitrary static interconnection networks with bursty background traffic having head‐of‐line priorities, complete buffer sharing and repetitive service blocking with random destination. The scheme facilitates inter‐process communication amongst parallel computers and grid computing networks as well as asynchronous transfer mode space division architectures and it is applicable to a single‐port mode of message passing communication. The scheme utilizes a queue‐by‐queue decomposition algorithm for arbitrary open queueing network models, based on the principle of maximum entropy, in conjunction with an information theoretic decomposition criterion and graph theoretic concepts. Evidence based on empirical studies indicates the suitability of the scheme for achieving an optimal one‐to‐all broadcasting cost. Copyright © 2004 John Wiley & Sons, Ltd.

An asymptotic queuing theoretic approach is proposed to analyze the performance of an FCFS (first-come, first-served) heterogeneous multiprocessor computer system with a single bus operating in a randomly changing environment. All stochastic times in the system are considered to be exponentially distributed and independent of the random environment, while the access and service rates of the processors are subject to random fluctuations. It is shown under the assumption of 'fast' arrivals that the busy period length of the bus converges weakly, under appropriate normalization, to an exponentially distributed random variable. As a consequence, main steady-state performance measures such as system throughput, mean delay time, expected waiting time, and mean number of active processors can be approximately determined. The reliability of the proposed method is validated by comparing the new approximations with known exact results.>

A new “hybrid” analytic framework, based on the principle of maximum entropy, is used to approximate the queue length distribution of a G/G/1 finite buffer queue. Robust recursive relations are derived and asymptotic connections to the infinite capacity queue are established. Furthermore, “equivalence” principles are applied to analyse two-stage cyclic queues with general service times and favourable comparisons with global balance solutions are made. Numerical examples provide useful information on how critically system behaviour is affected by the distributional form of interarrival and service patterns. It is shown that the maximum entropy solution predicts the bottleneck “anomaly” and also it defines bounds on system performance. Comments on the implication of the work to the analysis and aggregation of computer systems are included.

This paper studies the optimal blocking of magnetic files processed sequentially by jobs with fixed or variable amount of buffer storage available. Jobs have different running frequencies and are interrelated through common files. Non-linear models are used and a systematic approach is developed for the calculation of optimal block sizes. Alternative methods proposed by other authors are examined and favourable comparisons with the algorithm reported here are made. Comments on the implication of the results so far obtained are included.