Biblio

This article is a summary description of the Cognitive Packet Network (CPN) which is an example both of a completely software defined network (SDN) and of a self-aware computer network (SAN) which has been completely implemented and used in numerous experiments. CPN is able to observe its own internal performance as well as the interfaces of the external systems that it interacts with, in order to modify its behaviour so as to adaptively achieve objectives, such as discovering services for its users, improving their Quality of Service (QoS), reduce its own energy consumption, compensate for components which fail or malfunction, detect and react to intrusions, and defend itself against attacks.
 

The distinctive features of mobile ad hoc networks (MANETs), including dynamic topology and open wireless medium, may lead to MANETs suffering from many security vulnerabilities. In this paper, using recent advances in uncertain reasoning that originated from the artificial intelligence community, we propose a unified trust management scheme that enhances the security in MANETs. In the proposed trust management scheme, the trust model has two components: trust from direct observation and trust from indirect observation. With direct observation from an observer node, the trust value is derived using Bayesian inference, which is a type of uncertain reasoning when the full probability model can be defined. On the other hand, with indirect observation, which is also called secondhand information that is obtained from neighbor nodes of the observer node, the trust value is derived using the Dempster-Shafer theory (DST), which is another type of uncertain reasoning when the proposition of interest can be derived by an indirect method. By combining these two components in the trust model, we can obtain more accurate trust values of the observed nodes in MANETs. We then evaluate our scheme under the scenario of MANET routing. Extensive simulation results show the effectiveness of the proposed scheme. Specifically, throughput and packet delivery ratio (PDR) can be improved significantly with slightly increased average end-to-end delay and overhead of messages.

Automated server parameter tuning is crucial to performance and availability of Internet applications hosted in cloud environments. It is challenging due to high dynamics and burstiness of workloads, multi-tier service architecture, and virtualized server infrastructure. In this paper, we investigate automated and agile server parameter tuning for maximizing effective throughput of multi-tier Internet applications. A recent study proposed a reinforcement learning based server parameter tuning approach for minimizing average response time of multi-tier applications. Reinforcement learning is a decision making process determining the parameter tuning direction based on trial-and-error, instead of quantitative values for agile parameter tuning. It relies on a predefined adjustment value for each tuning action. However it is nontrivial or even infeasible to find an optimal value under highly dynamic and bursty workloads. We design a neural fuzzy control based approach that combines the strengths of fast online learning and self-adaptiveness of neural networks and fuzzy control. Due to the model independence, it is robust to highly dynamic and bursty workloads. It is agile in server parameter tuning due to its quantitative control outputs. We implemented the new approach on a testbed of virtualized data center hosting RUBiS and WikiBench benchmark applications. Experimental results demonstrate that the new approach significantly outperforms the reinforcement learning based approach for both improving effective system throughput and minimizing average response time.
 

In this paper we present WiMesh, a software tool we developed during the last ten years of research conducted in the field of multi-radio wireless mesh networks. WiMesh serves two main purposes: (i) to run different algorithms for the assignment of channels, transmission rate and power to the available network radios; (ii) to automatically setup and run ns-3 simulations based on the network configuration returned by such algorithms. WiMesh basically consists of three libraries and three corresponding utilities that allow to easily conduct experiments. All such utilities accept as input an XML configuration file where a number of options can be specified. WiMesh is freely available to the research community, with the purpose of easing the development of new algorithms and the verification of their performances.

This paper presents the relative merits of IR and microwave sensor technology and their combination with wireless camera for the development of a wall mounted wireless intrusion detection system and explain the phases by which the intrusion information are collected and sent to the central control station using wireless mesh network for analysis and processing the collected data. These days every protected zone is facing numerous security threats like trespassing or damaging of important equipments and a lot more. Unwanted intrusion has turned out to be a growing problem which has paved the way for a newer technology which detects intrusion accurately. Almost all organizations have their own conventional arrangement of protecting their zones by constructing high wall, wire fencing, power fencing or employing guard for manual observation. In case of large areas, manually observing the perimeter is not a viable option. To solve this type of problem we have developed a wall-mounted wireless fencing system. In this project I took the responsibility of studying how the different units could be collaborated and how the data collected from them could be further processed with the help of software, which was developed by me. The Intrusion detection system constitutes an important field of application for IR and microwave based wireless sensor network. A state of the art wall-mounted wireless intrusion detection system will detect intrusion automatically, through multi-level detection mechanism (IR, microwave, active RFID & camera) and will generate multi-level alert (buzzer, images, segment illumination, SMS, E-Mail) to notify security officers, owners and also illuminate the particular segment where the intrusion has happened. This system will enable the authority to quickly handle the emergency through identification of the area of incident at once and to take action quickly. IR based perimeter protection is a proven technology. However IR-based intrusion detection system is not a full-proof solution since (1) IR may fail in foggy or dusty weather condition & hence it may generate false alarm. Therefore we amalgamate this technology with Microwave based intrusion detection which can work satisfactorily in foggy weather. Also another significant arena of our proposed system is the Camera-based intrusion detection. Some industries require this feature to capture the snap-shots of the affected location instantly as the intrusion happens. The Intrusion information data are transmitted wirelessly to the control station via multi hop routing (using active RFID or IEEE 802.15.4 protocol). The Control station will receive intrusion information at real time and analyze the data with the help of the Intrusion software. It then sends SMS to the predefined numbers of the respective authority through GSM modem attached with the control station engine.