Symeon Papavassiliou

Integration of pricing with call admission control to meet QoS requirements in cellular networks

Call admission control (CAC) plays a significant role in providing the desired quality of service (QoS) in cellular networks. We investigate the role of pricing as an additional dimension of the call admission control process in order to efficiently and effectively control the use of wireless network resources. First, we prove that, for a given wireless network, there exists a new call arrival rate which can maximize the total utility of users while maintaining the required QoS. Based on this result and observation, we propose an integrated pricing and call admission control scheme where the price is adjusted dynamically based on the current network conditions in order to alleviate the problem of congestion. Our proposed integrated approach implicitly implements a distributed user-based prioritization mechanism by providing negative incentives according to the current network conditions and therefore shaping the aggregate traffic in the network. We compare the performance of our approach in terms of congestion prevention, achievable total user utility, and obtained revenue, with the corresponding results of conventional systems where pricing is not taken into consideration in the call admission control process. These performance results verify the considerable improvement that can be achieved by the integration of pricing in the call admission control process in cellular networks.

A mobility-based clustering approach to support mobility management and multicast routing in mobile ad-hoc wireless networks

In our proposed structure, mobile nodes are organized into nonoverlapping clusters which have adaptive variable-sizes according to their respective mobility. The mobility-based clustering (MBC) approach we are proposing uses a combination of both physical and logical partitions of the network (i.e. geographic proximity and functional relation between nodes, such as mobility pattern etc.)

On the optimal allocation of virtual resources in cloud computing networks

Cloud computing builds upon advances on virtualization and distributed computing to support cost-efficient usage of computing resources, emphasizing on resource scalability and on demand services. Moving away from traditional data-center oriented models, distributed clouds extend over a loosely coupled federated substrate, offering enhanced communication and computational services to target end-users with quality of service (QoS) requirements, as dictated by the future Internet vision. Toward facilitating the efficient realization of such networked computing environments, computing and networking resources need to be jointly treated and optimized. This requires delivery of user-driven sets of virtual resources, dynamically allocated to actual substrate resources within networked clouds, creating the need to revisit resource mapping algorithms and tailor them to a composite virtual resource mapping problem. In this paper, toward providing a unified resource allocation framework for networked clouds, we first formulate the optimal networked cloud mapping problem as a mixed integer programming (MIP) problem, indicating objectives related to cost efficiency of the resource mapping procedure, while abiding by user requests for QoS-aware virtual resources. We subsequently propose a method for the efficient mapping of resource requests onto a shared substrate interconnecting various islands of computing resources, and adopt a heuristic methodology to address the problem. The efficiency of the proposed approach is illustrated in a simulation/emulation environment, that allows for a flexible, structured, and comparative performance evaluation. We conclude by outlining a proof-of-concept realization of our proposed schema, mounted over the European future Internet test-bed FEDERICA, a resource virtualization platform augmented with network and computing facilities.

Combining Cloud and sensors in a smart city environment

In the current worldwide ICT scenario, a constantly growing number of ever more powerful devices (smartphones, sensors, household appliances, RFID devices, etc.) join the Internet, significantly impacting the global traffic volume (data sharing, voice, multimedia, etc.) and foreshadowing a world of (more or less) smart devices, or “things” in the Internet of Things (IoT) perspective. Heterogeneous resources can be aggregated and abstracted according to tailored thing-like semantics, thus enabling Things as a Service paradigm, or better a “Cloud of Things”. In the Future Internet initiatives, sensor networks will assume even more of a crucial role, especially for making smarter cities. Smarter sensors will be the peripheral elements of a complex future ICT world. However, due to differences in the “appliances” being sensed, smart sensors are very heterogeneous in terms of communication technologies, sensing features and elaboration capabilities. This article intends to contribute to the design of a pervasive infrastructure where new generation services interact with the surrounding environment, thus creating new opportunities for contextualization and geo-awareness. The architecture proposal is based on Sensor Web Enablement standard specifications and makes use of the Contiki Operating System for accomplishing the IoT. Smart cities are assumed as the reference scenario.

An entropy-based model for supporting and evaluating route stability in mobile ad hoc wireless networks

We propose an entropy-based modeling framework for supporting route stability in mobile ad hoc wireless networks. The basic motivations of the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The corresponding results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.

On the energy-efficient organization and the lifetime of multi-hop sensor networks

Due to hardware, energy, cost and other physical constraints, sensor-based networks present various design, implementation and deployment challenges. An analytical model is presented to estimate and evaluate the node and network lifetime in a randomly deployed multi-hop sensor network. Based on this, we provide a procedure for the creation of an energy efficient sensor network organization, that attempts to extend the lifetime of the communication critical nodes, and as a result the overall networks operational lifetime.

Network anomaly detection and classification via opportunistic sampling

In this article the emphasis is placed on the evaluation of the impact of intelligent flow sampling techniques on the detection and classification of network anomalies. Based on the observation that for specific-purpose applications such as anomaly detection a large fraction of information is contained in a small fraction of flows, we demonstrate that by using sampling techniques that opportunistically and preferentially sample traffic data, we achieve magnification of the appearance of anomalies within the sampled data set and therefore improve their detection. Therefore, the inherently lossy sampling process is transformed to an advantageous feature in the anomaly detection case, allowing the revealing of anomalies that would be otherwise untraceable, and thus becoming the vehicle for efficient anomaly detection and classification. The evaluation of the impact of intelligent sampling techniques on the anomaly detection process is based on the application of an entropy-based anomaly detection method on a packet trace with data that has been collected from a real operational university campus network.

A comprehensive resource management framework for next generation wireless networks

We propose an integrated resource management approach that can be implemented in next generation wireless networks that support multimedia services (data, voice, video, etc.). Specifically, we combine the use of position-assisted and mobility predictive advanced bandwidth reservation with a call admission control and bandwidth reconfiguration strategy to support flexible QoS management. We also introduce a mobile agent based framework that can be used to carry out the functions of geolocation and of the proposed resource management in wireless networks. A model is also developed to obtain the optimal location information update interval in order to minimize the total cost of the system operation. The comparison of the achievable performance results of our proposed scheme with the corresponding results of a conventional system that supports advanced bandwidth reservation only, as means of supporting the QoS requirements, demonstrate that our integrated scheme can alleviate the problem of overreservation, support seamless operation throughout the wireless network, and increase significantly the system capacity.

Diagnosing Anomalies and Identifying Faulty Nodes in Sensor Networks

In this paper, an anomaly detection approach that fuses data gathered from different nodes in a distributed sensor network is proposed and evaluated. The emphasis of this work is placed on the data integrity and accuracy problem caused by compromised or malfunctioning nodes. The proposed approach utilizes and applies Principal Component Analysis simultaneously on multiple metrics received from various sensors. One of the key features of the proposed approach is that it provides an integrated methodology of taking into consideration and combining effectively correlated sensor data, in a distributed fashion, in order to reveal anomalies that span through a number of neighboring sensors. Furthermore, it allows the integration of results from neighboring network areas to detect correlated anomalies/attacks that involve multiple groups of nodes. The efficiency and effectiveness of the proposed approach is demonstrated for a real use case that utilizes meteorological data collected from a distributed set of sensor nodes

A Cloud-Oriented Content Delivery Network Paradigm: Modeling and Assessment

Cloud-oriented content delivery networks (CCDNs) constitute a promising alternative to traditional content delivery networks. Exploiting the advantages and principles of the cloud, such as the pay as you go business model and geographical dispersion of resources, CCDN can provide a viable and cost-effective solution for realizing content delivery networks and services. In this paper, a hierarchical framework is proposed and evaluated toward an efficient and scalable solution of content distribution over a multiprovider networked cloud environment, where inter and intra cloud communication resources are simultaneously considered along with traditional cloud computing resources. To efficiently deal with the CCDN deployment problem in this emerging and challenging computing paradigm, the problem is decomposed to graph partitioning and replica placement problems while appropriate cost models are introduced/adapted. Novel approaches on the replica placement problem within the cloud are proposed while the limitations of the physical substrate are taken into consideration. The performance of the proposed hierarchical CCDN framework is assessed via modeling and simulation, while appropriate metrics are defined/adopted associated with and reflecting the interests of the different identified involved key players.