Murat Karakaya

Free Riding in Peer-to-Peer Networks

Free riding in peer-to-peer (P2P) networks poses a serious threat to their proper operation. Here, the authors present a variety of approaches developed to overcome this problem. They introduce several unique aspects of P2P networks and discuss free ridings effects on P2P services. They categorize proposed solutions and describe each categorys important features and implementation issues together with some sample solutions. They also discuss open issues, including common attacks and security considerations.

Counteracting free riding in Peer-to-Peer networks

The existence of a high degree of free riding is a serious threat to Peer-to-Peer (P2P) networks. In this paper, we propose a distributed framework to reduce the adverse effects of free riding on P2P networks. Our solution primarily focuses on locating free riders and taking actions against them. We propose a framework in which each peer monitors its neighbors, decides if they are free riders, and takes appropriate actions. Unlike other proposals against free riding, our framework does not require any permanent identification of peers or security infrastructures for maintaining a global reputation system. Our simulation results show that the framework can reduce the effects of free riding and can therefore increase the performance of a P2P network.

Clustering Mobile Trajectories for Resource Allocation in Mobile Environments

The recent developments in computer and communication technologies gave rise to Personal Communication Systems. Due to the nature of the PCS, the bandwidth allocation problem arises, which is based on the notion of bandwidth-on-demand. We deal with the problem of how to predict the position of a mobile client. We propose a new algorithm, called DCP, to discover user mobility patterns from collections of recorded mobile trajectories and use them for the prediction of movements and dynamic allocation of resources. The performance of the proposed algorithm is examined against two baseline algorithms. The simulation results illustrate that the proposed algorithm achieves recall that is comparable to that of the baseline algorithms and substantial improvement in precision. This improvement guarantees very good predictions for resource allocation with the advantage of very low resource consumption.

A distributed and measurement-based framework against free riding in peer-to-peer networks

We propose a distributed and measurement-based method to reduce the degree of free riding in P2P networks. We primarily focus on developing schemes to locate free riders and on determining policies that can be used to take actions against them. Our proposed schemes require each peer to monitor its neighboring peers, make decisions if they exhibit any kind of free riding, and take appropriate actions if required.

Evaluation of a Broadcast Scheduling Algorithm

One of the two main approaches of data broadcasting is pull-based data delivery. In this paper, we focus on the problem of scheduling data items to broadcast in such a pull-based environment. Previous work has shown that the Longest Wait First heuristic has the best performance results compared to all other broadcast scheduling algorithms, however the decision overhead avoids its practical implementation. Observing this fact, we propose an efficient broadcast scheduling algorithm which is based on an approximate version of the Longest Wait First heuristic. We also compare the performance of the proposed algorithm against well-known broadcast scheduling algorithms.

A connection management protocol for promoting cooperation in Peer-to-Peer networks

The existence of a high degree of free riding in Peer-to-Peer (P2P) networks is an important threat that should be addressed while designing P2P protocols. In this paper we propose a connection-based solution that will help to reduce the free riding effects on a P2P network and discourage free riding. Our solution includes a novel P2P connection type and an adaptive connection management protocol that dynamically establishes and adapts a P2P network topology considering the contributions of peers. The aim of the protocol is to bring contributing peers closer to each other on the adapted topology and to push the free riders away from the contributors. In this way contribution is promoted and free riding is discouraged. Unlike some other proposals against free riding, our solution does not require any permanent identification of peers or a security infrastructure for maintaining a global reputation system. It is shown through simulation experiments that there is a significant improvement in performance for contributing peers in a network that applies our protocol.

Efficient route planning for an unmanned air vehicle deployed on a moving carrier

Vehicle routing problem (VRP) is a constrained extension of the well-known traveling salesman problem (TSP). Emerging from the current conceptual trends in operations field, a new constraint to be included to the existing VRP parameters is the depot mobility. A practical example of such a problem is planning a route for an Unmanned air vehicle (UAV) deployed on a mobile platform to visit fixed targets. Furthermore, the range constraint of the UAV becomes another constraint within this sample case as well. In this paper, we define new VRP variants by introducing depot mobility (Mobile Depot VRP: MoDVRP) and extending it with capacity constraint (Capacitated MoDVRP: C-MoDVRP). As a sample use case, we study route planning for a UAV deployed on a moving carrier. To deal with the C-MoDVRP, we propose a Genetic Algorithm that is adapted to satisfy the constraints of depot mobility and range, while maximizing the number of targets visited by the UAV. To examine the success of our approach, we compare the individual performances of our proposed genetic operators with conventional ones and the performance of our overall solution with the Nearest Neighbor and Hill Climbing heuristics, on some well-known TSP benchmark problems, and receive successful results.

Deadline-Aware Energy-Efficient Query Scheduling in Wireless Sensor Networks with Mobile Sink

Mobile sinks are proposed to save sensor energy spent for multihop communication in transferring data to a base station (sink) in Wireless Sensor Networks. Due to relative low speed of mobile sinks, these approaches are mostly suitable for delay-tolerant applications. In this paper, we study the design of a query scheduling algorithm for query-based data gathering applications using mobile sinks. However, these kinds of applications are sensitive to delays due to specified query deadlines. Thus, the proposed scheduling algorithm aims to minimize the number of missed deadlines while keeping the level of energy consumption at the minimum.

Ontology-supported enterprise architecture analysis

Today, processing integrated information within and between enterprises is increasingly becoming more and more critical, and so is the implementation and evaluation of an Enterprise Architecture (EA). The review of literature on EA evaluation shows several issues. However, the evaluation of EAs has not attracted sufficient attention, and thus, this research area has not been explored thoroughly yet. We believe that in order to ensure consistency, interoperability and computational inferences among EAs, a complete and holistic approach, rather than monolithic, should be developed. Therefore, in this study, we propose an ontology-supported process model for the evaluation of EAs, and present the implementation details. The main contributions of the present study are the improvements realized in the expressiveness, extensibility, and computable power of EAs, and their evaluation techniques. Although the proposed model requires gathering empirical evidences and investigating applications in concrete cases, the first implications of the proposed model indicates its validity and feasibility, and, hence, the initial results are promising for continuing future studies.

An IoT application for locating victims aftermath of an earthquake

This paper presents an Internet of Things (IoT) framework which is specially designed for assisting the research and rescue operations targeted to collapsed buildings aftermath of an earthquake. In general, an IoT network is used to collect and process data from different sources called things. According to the collected data, an IoT system can actuate different mechanisms to react the environment. In the problem at hand, we exploit the IoT capabilities to collect the data about the victims before the building collapses and when it falls down the collected data is processed to generate useful reports which will direct the search and rescue efforts. The proposed framework is tested by a pilot implementation with some simplifications. The initial results and experiences are promising. During the pilot implementation, we observed some issues which are addressed in the proposed IoT framework properly.