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The Internet of Battlefield Things is a relatively new cyberphysical system and even though it shares a lot of concepts from the Internet of Things and wireless ad hoc networking in general, a lot of research is required to address its scale and peculiarities. In this article we examine a fundamental problem pertaining to the routing/dissemination of information, namely the construction of a backbone. We model an IoBT ad hoc network as a multilayer network and employ the concept of domination for multilayer networks which is a complete departure from the volume of earlier works, in order to select sets of nodes that will support the routing of information. Even though there is huge literature on similar topics during the past many years, the problem in military (IoBT) networks is quite different since these wireless networks are multilayer networks and treating them as a single (flat) network or treating each layer in isolation and calculating dominating set produces submoptimal or bad solutions; thus all the past literature which deals with single layer (flat) networks is in principle inappropriate. We design a new, distributed algorithm for calculating connected dominating sets which produces dominating sets of small cardinality. We evaluate the proposed algorithm on synthetic topologies, and compare it against the only two existing competitors. The proposed algorithm establishes itself as the clear winner in all experiments.

This paper presents the preliminary results of the THEASIS system which is under development for early detection of wildfires in Greece. Firstly, the proposed system in terms of conceptual design, the early fire detection methodology as well as the main software modules are presented. Laboratory and small-scale experiments made in the University of Patras campus as well as in the Strofylia forest are presented. The concluding remarks are promising towards the development of an efficient system for early detection of wildfires.

Monitoring and maintaining communications in a multilayer ad hoc wireless network requires a stable communication overlay. Such monitoring should be resilient, avoiding reliance on a single (or a few) layers, and energy-aware, not being vulnerable to the exhaustion of available energy in a single network element. Thus, there is possibly a trade-off between overlay size, interlayer connectivity, and the energy distribution within the overlay. In this paper, we present three distributed energy-aware multilayer connected edge dominating set algorithms, show how they manage such trade-offs in practical scenarios, and show that CCEDS, a pruned centrality-based distributed algorithm, has the best performance.

Next-location prediction in a VANET system, where each vehicle acts as a network node, is of great importance in intelligent transport systems (ITS) as this property could have a direct and positive effect on network connectivity, traffic management and hence, improve overall ITS safety. In the last few years, the widespread use of GPS navigation systems and wireless communication technology-enabled vehicles has resulted in huge volumes of trajectory data. The task of utilizing this data employing pattern-matching techniques for next-location prediction in an efficient and accurate manner is an ongoing research problem. This paper presents the Rich-Dictionary Markov Predictor (RDM), a protocol for producing online these forecasts by using a pattern matching technique. RDM is fast, accurate and fully parameterized presenting different trade-offs as regards efficiency versus prediction accuracy. We evaluated the effectiveness of RDM via simulation and the results attest that it achieves on the average more than 35% better prediction accuracy and competitive to faster prediction times than other model independent and highly accurate prediction algorithms.

Modeling Big Data Applications is a key research topic for designing, analyzing, programming and deploying data-intensive applications, with high value and long-term trade-offs. The need for unified perspectives, architectures and requirements techniques is requisite. The current approach proposes the use of Feature Models to fill this gap by extending present model-driven engineering practices with utter purpose to define a reusable, extensible and highly configurable design approach for Big Data Applications.

Modern battlefields are characterized by increasing deployment of ad hoc communications among allied entities. These networks can be seen as a complex multi-layer ad hoc network, where each layer may be an independently acting soldiers' group, a group of drones, helicopters, vehicles and so on. Building a backbone network for these environments, which will guarantee efficient communication among all nodes (i.e., network-wide broadcasting) is of fundamental significance for the dissemination of information. In this article we generalize the concept of connected dominating sets for multi-layer networks and use them as the network backbone. We propose efficient methods to identify nodes that are efficient cross-layer spreaders along with a distributed algorithm to build the connected dominating set. Due to the lack of competing methods in the literature, we compare the proposed methods against some baseline methods and investigate the performance of all algorithms for a variety of multi-layer network topologies, illustrating their advantages and disadvantages; the result of the evaluation identifies the clPCI method of recognizing efficient cross-layer spreaders as the champion method.

Vehicular networks have a diverse range of applications that vary from safety, to traffic management and comfort. Vehicular communications (VC) can assist in the ecorouting of vehicles in order to reduce the overall mileage and CO2 emissions by the exchange of data among vehicle-entities. However, the trustworthiness of these data is crucial as false information can heavily affect the performance of applications. Hence, the devising of mechanisms that reassure the integrity of the exchanged data is of utmost importance. In this article we investigate how tweaked information originating from malicious nodes can affect the performance of a real time eco routing mechanism that uses DSRC communications, namely ErouVe. We also develop and evaluate defense mechanisms that exploit vehicular communications in order to filter out tweaked data. We prove that our proposed mechanisms can restore the performance of the ErouVe to near its optimal operation and can be used as a basis for protecting other similar traffic management systems., 8 pages, 8 figures

With the emergence of Online Social Networks (OSNs), as the most popular medium for advertisements, as source of knowledge and information, the emergence of malicious contents (viruses, false rumors, etc‥) has become a critical issue that requires immediate attention. In this study we investigate on blocking the contagion of malicious things dynamically, by continuously fighting the diffusion near the source of misinformation under the Susceptible-Infectious-Recovered (SIR) model. We focus on protecting networked populations by removing key connections between nodes, and show via experimental results, that by following the infection the contagion can be controlled more efficiently and even being stopped in the earliest steps. We modify a well studied heuristic from the literature of graphs, and show that our proposed technique significantly outperforms what we believe the state-of-the-art competitors by successfully confronting the infection in real networks.

This paper examines intelligent lane change models based on the cooperation among connected vehicles for traffic management and travel time optimization. Lane change decisions and speed controls could be coordinated and optimized to reduce the overall braking and achieve greater traffic throughput. In an effort to design a distributed cooperative lane change assistant (D-CLCA) within the European Commission's project REDUCTION∗, this paper describes the requirements associated with an optimal lane change behavior, and evaluate existing lane change models based on these requirements. These models are evaluated for travel times, fuel consumption, number of lane changes and the overall braking globally for all vehicles on the considered road segment. We have developed traffic simulations using different traffic densities for both symmetric and asymmetric lane changes and different levels of cooperation among vehicles. Our empirical analysis shows that an optimal lane change model should optimize the conflicting requirements of maintaining desired speeds and reducing the number of lane changes and fuel consumption for all vehicles simultaneously. These results will be used to develop an intelligent distributed and cooperative lane change assistant.

The NITOS wireless testbed, is one of the main building blocks in the wireless testbed experimentation, offered by the FIRE community, and a core Fed4Fire partner. Its main focus is on wireless accessed technologies and on all layers of the protocol stack. In the rapidly changing technological environ-ment, a unique opportunity is provided to enhance the NITOS testbed with cloud computing experimentation capabilities and increase the heterogeneity and diversity of possible services that can be offered to experimenters/ developers. In this paper we describe the NITOS approach on adopting cloud technologies and SDN capabilities and how we upgrade the meaning of “delivered service” in testbed experimentation using SOA extensions.

Social network analysis comprises a popular set of tools for the analysis of online social networks. Among these techniques, k-shell decomposition of a graph is a popular technique that has been used for centrality analysis, for communities discovery, for the detection of influential spreaders, and so on. The huge volume of input graphs and the environments where the algorithm needs to run i.e., large datacenters, makes none of the existing algorithms appropriate for the decomposition of graphs into shells. In this article, we develop for the first time in the literature, a distributed algorithm based on MapReduce for the k-shell decomposition of a graph. We furthermore, provide an implementation and assessment of the algorithm using real social network datasets. We analyze the tradeoffs and speedup of the proposed algorithm and conclude for its virtues and shortcomings.

Inter-Vehicle Communication is expected to be widely adopted during the next years by the car industry, enabling Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication targeting at safer commuting. Therefore, the research community have been working towards providing a robust communication solution that will interoperate with existing network infrastructure and will provide an effective way of communicating using location information. One of the proposed solutions is the GeoNetworking protocol, standardized by ETSI, using location based addresses and an IPv6 adaptation sublayer for communicating with the Internet. Several implementations of the protocol exist currently, however most of them are integrated in simulation environments, thus ignoring several factors induced when experimenting under real conditions. In this paper we present our own implementation of an ETSI compliant GeoNetworking protocol and its integration in the NITOS Future Internet facility that enables open and remote access to experimenters on a 24/7 basis. This is the first real implementation in an open wireless testbed, which offers to the research community high diversity in the configuration parameters of their ITS experiments. We further explain our extensions that enable real world testing of our protocol implementation and we finally evaluate our solution in a real large scale wireless setup.

In the overall effort of reducing CO2 emissions especially in large cities vehicular communications can play an important role. Intelligent transportation systems, which aim to use information and communication technology are considered to be a major factor in this effort. Eco-routing is already used to suggest most environmental-friendly routes in order to reduce overall mileage and CO2 emissions based on historical data. In this paper we propose a real time system based on Dedicated short-range communication (DSRC) capabilities in order to reroute vehicles to the most ecological route, avoiding congested roads and minimizing the overall travel time and C02 emissions.

Clustering of Vanets is a technique for grouping nodes in geographical vicinity together, making the network more robust and scalable. Clustering of vehicles that is based on virtual forces has been recently introduced for highways. We propose a new algorithm, called Virtual Forces Vehicular Clustering (VFVC), to create stable clusters in Urban environments where mobility patterns of vehicles is more spatial. The algorithm uses combined metrics produced by vehicle's position, geometry, relative velocity and vehicle's lane in order to assign virtual forces among them and create clusters. The performance of the proposed algorithm is examined against two baseline algorithms and Spring clustering (Sp - Cl). Results obtained show that VFVC performs better with a significant increase in cluster stability.

In the present paper methods of controlling Corona and breakdown in small rod-plate air gaps are investigated. Combining experimental and simulation-theoretical work, it is resulted that when the rod's diameter is bigger, the gap length larger and the rod is grounded the field is less inhomogeneous. Therefore the value of the dc breakdown voltage without Corona is higher. If Corona occurs then the values of the Corona onset voltage are higher, and the corona effects are not intense. The Corona effects, lead to a rise of the value of the dc breakdown voltage especially when the rod is negatively charged. Moreover an insulated thin barrier, when positioned near the rod increases the breakdown dc voltage to a maximum value, and minimizes the Corona effects. Especially for gaps stressed by impulse voltage the Corona effects, appearing with the form of electric current pulses, are influenced by the same factors with a different way. The values of the breakdown voltage in contrast to what happens with dc voltage are higher when the Corona effects are weaker, depending on the influence of the field's inhomogenity (geometry and effect of grounding). It is also resulted that a resistor connected in series with the gap decreases its maximum charging voltage and increases the value of the breakdown voltage.

The deployment of wireless sensor networks in many application areas like environment control, target tracking in battlefields, requires an optimization to the communication among the sensors so as to serve data in short latency and with minimal energy consumption. Cooperative data caching has been proposed as an effective and efficient technique to achieve these goals concurrently. The design of protocols for such networks depends mainly on the selection of the sensors which will take special roles in coordinating the procedure of caching and take forwarding decisions. This article introduces a new metric to aid in the selection of such nodes. Based on this metric, we propose a new energy efficient cooperative caching protocol, which is compared against the state-of-the-art competing protocol. The simulation results attest the superiority of the proposed protocol.

Clustering in vanets is of crucial importance in order to cope with the dynamic features of the vehicular topologies. Algorithms that give good results in Manets fail to create stable clusters since vehicular nodes are characterized by their high mobility and the different mobility patterns that even nodes in proximity may follow. In this paper, we propose a distributed clustering algorithm which forms stable clusters based on force directed algorithms. The simulation results show that our Spring-Clustering (Sp-Cl) scheme has stable performance in randomly generated scenarios on a highway. It forms lesser clusters than Lowest-ID and it is better in terms of Cluster stability compared to Lowest-ID and LPG algorithms in the same scenarios.

Wireless data broadcast received a lot of attention from industries and academia in recent years. In any form of a push-based broadcast, access latency and tuning time are vital issues, and in order to address the tradeoff among these competing goals, the broadcasting of indices along with the data is the most viable solution. Currently, two broad indexing families exist: those that exploit some form of a tree structure, and those that are based on some ‘distributed access on the air’ mechanism. The latter family is the most popular and viable, because it allows for following ‘air-pointers’ without the need to first find a tree root. The champion method of the distributed air index is the Exponential index which however is not appropriate when the access pattern is skewed, i.e., some data items are more popular than the others. To address this shortcoming, we design a Distributed Skip Air Index (DiSAIn), which exploits access statistics in order to improve average tuning time, while it preserves the access latency equal to that of the original Exponential index. To attest the superiority of the proposed indexing method, we perform a detailed simulation evaluation of the two competing methods.

Efficient querying of huge volumes of multidimensional data stored in cloud computing systems has become a necessity, due to the widespread of cloud storage facilities. With clouds getting larger and available data growing larger and larger it is mandatory to develop fast, scalable and efficient indexing schemes. In this paper, we propose the A-tree, a distributed indexing scheme for multidimensional data capable of handling both point and range queries, appropriate for cloud computing environments. A performance evaluation of the A-tree against the state-of-the-art competitor attests its superiority, achieving significantly lower latencies.

Packet scheduling in wireless ad hoc networks is a fundamental problem for ad hoc networking. Backpressure scheduling is a solid and throughput optimal policy for such networks, but suffers from increased delays. In this article, we present an holistic approach to improve upon the delay problems of backpressure-type algorithms. We develop two scheduling policies, namely Voting-based and Layered backpressure routing which both are throughput optimal. We experimentally compare the proposed policies against all the delay-aware backpressure policies and conclude that Layered backpressure is a high performance policy compromising a little delay for robustness, low computational complexity and simplicity.

In current publish/subscribe networks messages are not stored and only active subscribers receive published messages. However, in a dynamic scenario a user may be interested in content published before the subscription time. In this paper, we introduce a mechanism that enables storing in such networks, while maintaining the main principle of loose-coupled and asynchronous communication. Furthermore, we propose a new storage placement and replication algorithm which differentiates classes of content and minimize the clients response latency. The performance of our proposed placement and replication algorithm and the proposed storing mechanism is evaluated via simulations and insights are given for future work.

Cloud computing is a recent trend in IT that moves computing and data away from desktop and portable PCs into large data centers, and outsources the “applications” (hardware and software) as services over the Internet. Cloud computing promises to increase the velocity with which applications are deployed, increase innovation, and lower costs, all while increasing business agility. But, is the migration to the Cloud the most profitable option for every business? This article presents a study of the basic parameters for estimating the potential costs deriving from building and deploying applications on cloud and on-premise assets.

Storage management in wireless sensor networks is an area that has started to attract significant attention, and several methods have been proposed, such as Local Storage (LS), Data-Centric Storage (DCS) and more recently Location-Centric Storage (LCS). Several modern applications, like context-dependent information dissemination for pervasive computing, on-demand warning in surveillance sensor networks and roadway safety warning, require that each originating event is stored around its point of origin. LCS is a suitable approach for such applications. Though, LCS does not take into consideration the origin of the queries,which is equally important to the storage method, because it has immediate influence on the experienced latency. This paper proposes a simple yet effective way of reducing the network latency, namely the Query Sensitive Storage (QSS) protocol. QSS makes certain that not only will the queries be answered, but all subsequent queries that originated in the same area will be answered faster. The experimental evaluation using the J-Sim simulator attests that with the proposed QSS protocol we can achieve smaller network latency at a minimum storage cost as compared to its state-of-the-art competitor, namely LCS.

This paper considers the problem of finding the most central nodes in neighborhoods of a given network with directed or undirected links taking into account only local information. An algorithm that calculates ranking, taking into account the n-hop neighborhood of each node is proposed. The method is compared to popular existing schemes for ranking, using Spearman's rank correlation coefficient and other metrics. An extension to a faster algorithm which reduces the size of the examined network is described as well

Metasearch engines are a significant part of the information retrieval process. Most of Web users use them directly or indirectly to access information from more than one data sources. The cornerstone of their technology is their rank aggregation method, which is the algorithm they use to classify the collected results. In this paper we present three new rank aggregation methods. At first, we propose a method that takes into consideration the regional data for the user and the pages and assigns scores according to a variety of user defined parameters. In the second expansion, not all component engines are treated equally. The user is free to define the importance of each engine by setting appropriate weights. The third algorithm is designed to classify pages having URLs that contain subdomains. The three presented methods are combined into a single, personalized scoring formula, the global KE. All algorithms have been implemented in QuadSearch, an experimental metasearch engine available at http://quadsearch.csd.auth.gr.

It is a great pleasure to welcome you to the 2008 IPS/UMS/WNGS/MUS workshop held in conjunction with the International Conference on Multimedia and Ubiquitous Engineering (MUE2008), Hanwha Resort Haeundae, Busan, Korea. The workshop covers topics on ubiquitous multimedia services and security in ubiquitous multimedia systems. All the submitted papers have undergone rigorous review process by the technical program committee members and external reviewers. We have selected 17 best papers for presentation and publication in the conference proceedings.

The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Quite a lot of node clustering techniques have appeared in the literature, and roughly fall into two families; those based on the construction of a dominating set and those which are based solely on energy considerations. The former family suffers from the fact that only a small subset of the network nodes are responsible for relaying the messages, and thus cause rapid consumption of the energy of these nodes. The later family uses the residual energy of each node in order to direct its decision about whether it will elect itself as a leader of a cluster or not. This family's methods ignore topological features of the nodes and are used in combination with the methods of the former family. We propose a novel distributed clustering protocol for wireless sensor networks, based on a novel metric for characterizing the importance of a node, w.r.t. its contribution in relaying messages. The protocol achieves small communication complexity and linear computation complexity. Experimental results for various sensor network topologies show that the protocol generates only a few clusters, guaranteeing a small number of message relays thus improving network lifetime

Energy conservation and access efficiency are two fundamental though competing goals in broadcast wireless networks. To tackle the energy penalty from sequential searching, the interleaving of index with data items has been proposed. Although, quite important contributions exist on providing broadcast indexes, they have one or more of the following problems. Firstly, all of them assume total ordering among broadcast data, and none considers the more general case of partial ordering. Secondly, they are balanced structure, which does not fit the "linear (one-dimensional) structure" of the wireless medium, in which imbalanced structures may offer significant advantages. Thirdly, they do not take into account the skewness in the access pattern, which prohibits larger performance gains to be reaped. Finally, they require all index items to be of equal size, which may not always give the optimal performance. To cope with all these problems, we introduce a new imbalanced tree-structured index. The new index is shown to be a generalization of two previously proposed high-performance indexes, and it introduces for the first time the problem of indexing partially ordered broadcast data. We present an experimental analysis of the proposed method, contrasting it with competing techniques. The analysis exhibits the efficiency of the proposed index in reducing the energy consumption without noticeably worsening the access latency

Broadcasting is an effective means for disseminating information in wireless ad hoc networks. In this paper we propose a novel distributed broadcasting protocol in wireless ad hoc networks, which is based on an highly efficient metric for characterizing the importance of a node, with respect to its contribution in covering the local neighborhood. The protocol is reliable and achieves small communication complexity with linear in the number of nodes computation complexity. Experimental results for a large variety of network topologies show that the proposed algorithm is capable of generating small connected dominating sets, which guarantee a relatively small number of rebroadcasts.