Empirical evaluation of accuracy of mathematical software used for availability assessment of fault-tolerant computer systems

Dependability assessment is typically based on complex probabilistic models. Markov and semi-Markov models are widely used to model dependability of complex hardware/software architectures. Solving such models, especially when they are stiff, is not trivial and is usually done using sophisticated mathematical software packages. We report a practical experience of comparing the accuracy of solutions stiff Markov models obtained using well known commercial and research software packages. The study is conducted on a contrived but realistic cases study of computer system with hardware redundancy and diverse software under the assumptions that the rate of failure of software may vary over time, a realistic assumption. We observe that the disagreement between the solutions obtained with the different packages may be very significant. We discuss these findings and directions for future research

Checkpointing algorithms and fault prediction

This paper deals with the impact of fault prediction techniques on checkpointing strategies. We extend the classical first-order analysis of Young and Daly in the presence of a fault prediction system, characterized by its recall and its precision. In this framework, we provide an optimal algorithm to decide when to take predictions into account, and we derive the optimal value of the checkpointing period. These results allow to analytically assess the key parameters that impact the performance of fault predictors at very large scale.Comment: Supported in part by ANR Rescue. Published in Journal of Parallel and Distributed Computing. arXiv admin note: text overlap with arXiv:1207.693

An analysis on decentralized adaptive MAC protocols for Cognitive Radio networks

The scarcity of bandwidth in the radio spectrum has become more vital since the demand for more and more wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum and inefficiency in its utilization has been smartly addressed by the Cognitive Radio (CR) Technology which is an opportunistic network that senses the environment, observes the network changes, and then using knowledge gained from the prior interaction with the network, makes intelligent decisions by dynamically adapting their transmission characteristics. In this paper some of the decentralized adaptive MAC protocols for CR networks have been critically analyzed and a novel adaptive MAC protocol for CR networks, DNG-MAC which is decentralized and non-global in nature, has been proposed. The results show the DNG-MAC out performs other CR MAC protocols in terms of time and energy efficiency

SDN management layer: design requirements and future direction

Computer networks are becoming more and more complex and difficult to manage. The research community has been expending a lot of efforts to come up with a general management paradigm that is able to hide the details of the physical infrastructure and enable flexible network management. Software Defined Networking (SDN) is such a paradigm that simplifies network management and enables network innovations. In this survey paper, by reviewing existing SDN management layers (platforms), we identify the general common management architecture for SDN networks, and further identify the design requirements of the management layer that is at the core of the architecture. We also point out open issues and weaknesses of existing SDN management layers. We conclude with a promising future direction for improving the SDN management layer.This work is supported in part by the National Science Foundation (NSF grant CNS-0963974)

Securing Our Future Homes: Smart Home Security Issues and Solutions

The Internet of Things, commonly known as IoT, is a new technology transforming businesses, individuals’ daily lives and the operation of entire countries. With more and more devices becoming equipped with IoT technology, smart homes are becoming increasingly popular. The components that make up a smart home are at risk for different types of attacks; therefore, security engineers are developing solutions to current problems and are predicting future types of attacks. This paper will analyze IoT smart home components, explain current security risks, and suggest possible solutions. According to “What is a Smart Home” (n.d.), a smart home is a home that always operates in consideration of security, energy, efficiency and convenience, whether anyone is home or not