Ad Hoc Networks

Daily roadway commutes provide driving patterns in time and in space motivating the formation of mobile vehicular groups based on common backgrounds and interests. These groups can be used to reduce the propagation of irrelevant and redundant information and can be used also for group-based applications such as caravaning. This paper investigates the groups formation behavior under the dynamic topology of vehicular networks through different traces and synthetic scenarios. Next, to show the impact of group on content dissemination scheduling, a comparison of group-based scheduling with other relevant data dissemination scheduling schemes is conducted by simulations in terms of delivery ratio and latency. Simulation results show that groups can be used in order to share information in an intelligent way such that to reduce the propagation of irrelevant and redundant information. Additionally, this paper shows that group-based data dissemination can enhance the delivery ratio and latency compared to other relevant scheduling schemes.

Using WLAN-hotspots to provide access to mobile users has proven its feasibility and interest in many cases such as mesh and vehicular networks. Nevertheless, VANETs are still looking for deployment strategies that would ensure a maximum data exchange and a well balanced access. The high mobility and density of users and the impossibility to provide a full coverage make such requirements a hard challenge.

In this paper we make a quick review of the commonly used deployment schemes and show their limits regarding real VANETs constraints. We analyze the deployment problem taking into account the vehicular density and the resulting contention problem. We formalize the problem and provide a centrality-based deployment aiming a global service-access optimization and a p-center based deployment aiming fairness as a second objective. We evaluate through simulation the performance of our proposed schemes and show their efficiency and benefits in comparison to other deployment strategies.

The spreading of messages in a vehicular network is an important task and finds many applications in Intelligent Transportation Systems (ITS). A common problem to this direction is to select an appropriate set of vehicles that on behalf of a sender will further rebroadcast the message and reduce redundant retransmission. Of particular interest is the use of social inspired metrics to identify potent vehicles which can set the right path for the spreading of messages and cover a wide range of a vehicular network. In this work we propose a novel approach for selecting vehicles based on the Probabilistic Control Centrality (pCoCe), which accounts for the number of directed and diverse paths emanating from each individual vehicle. We evaluated our approach and compared with the standard IETF, Optimized Link State Routing Protocol (OLSR). Our experimental results show that pCoCe outperforms its competitor in various network conditions by at least 10%.

Significant advances in wireless communication technologies and mobile devices have led to their widespread use. For example, the so-called Intelligent Transportation Systems (ITS), which encompass a wide range of advanced applications for transportation, have attracted a lot of attention. In this context, one could think that software agents, which can have properties such as intelligence and autonomy, are expected to play a key role. But is this the case? Are they being used in work related to ITS and/or vehicular networks? Could they really provide benefits? In this paper, we analyze the state of the art and draw some conclusions about the potential interest of mixing these two fields.

A wireless sensor network (WSN) typically consists of base stations and a large number of wireless sensors. The sensory data gathered from the whole network at a certain time snapshot can be visualized as an image. As a result, information hiding techniques can be applied to this “sensory data image”. Steganography refers to the technology of hiding data into digital media without drawing any suspicion, while steganalysis is the art of detecting the presence of steganography. This article provides a brief review of steganography and steganalysis applications for wireless sensor networks (WSNs). Then we show that the steganographic techniques are both related to sensed data authentication in wireless sensor networks, and when considering the attacker point of view, which has not yet been investigated in the literature. Our simulation results show that the sink level is unable to detect an attack carried out by the nsF5 algorithm on sensed data.

Modeling malware spreading in wireless networks has attracted significant interest lately, since this will increase the robustness of such networks that constitute the lion’s share of Internet access nowadays. However, all of previous works have considered networks with fixed number of devices. In this work, we focus on users that can dynamically join and leave the network (node churn) as a result of the effects of malware, or their own operation, i.e. energy depletion. We adopt and adapt a queuing-based model for malware spreading for the case of wireless distributed networks with churn. The corresponding methodology captures the dynamics of SIS-type malware, where nodes are always prone to receive new or already spreading infections over a long period. The employed framework can be exploited for quantifying network reliability and study network behavior, which can be further used for increasing the robustness of the system against the most severe attacks.

Electrification is foremost actor in superseding internal combustion engine vehicles with electric vehicles (EV). The EV technology will lead to fundamental shift in existing power grid as well as transportation systems. In Smart grid, EVs play vital roles to reduce dependence on fossil fuel, in turn, minimize green house gas emissions. In Vehicle-to-Grid (V2G) network, EVs communicate with power grid operators to trade demand response services by delivering stored electricity into the electric power grid. Communication between aggregator and EVs is central for such an approach. Viewing security and privacy requirements for V2G communications, privacy-preserving technique is central for efficacious V2G network implementation. In this paper, we have proposed effective security and privacy-preserving mechanism for aggregator based V2G network, which is built on ECC-based restrictive partially blind signature. We have provided security analysis and shown that the proposed mechanism is efficient than existing ones in terms of computational overheads.

Reducing the energy consumption and improving the robustness of a Wireless Sensor Network (WSN) are the main requirements for many industrial and research applications. The sensors usually use a routing protocol in order to deliver the sensing data to a Base Station (BS) which may be far away from the monitoring area. Many algorithms proposed in the literature compute the routing process by clustering the network and by designing new election mechanisms in which the cluster-heads are chosen taking account of the remaining energy, the communication cost and the density of nodes. However, they do not consider the connectivity to the BS, and assume that all the nodes or only few prefixed nodes are able to directly communicate with it. We believe that this assumption is not suitable for many applications of WSN and to tackle this problem we propose CESAR, a multi-hop and energy-efficient routing protocol for large-scale WSN which includes a new cluster-head selection mechanism aware of the battery level and the connectivity to the BS. Furthermore, our solution employs an innovative hybrid approach to combine both clustering and on-demand techniques in order to provide an adaptive behavior for different dynamic topologies. Simulation results show that our solution outperforms in terms of energy consumption and data delivery other known routing algorithms in the literature.

In our area of Mobile Multimedia, the expansion of wireless networks is dazzling and mobility has become a major issue exacerbated by the significant increase in the number of mobile users. A node operating in a basic mobile network behaves the same way a blind person moving in our universe by developing his own representation with his stick, a mechanism known in the literature as terminal mobility. To reduce this blindness, several methods have been developed that are based on community behavior. One of the facets of the use of community behavior is the integration of the faculty of “perception” of groups in social communities at the heart of a routing protocol for mobile networks.

We propose a routing protocol based on the original Optimized Link State Routing protocol (OLSR) to which we add the component of social perception of groupings of individuals. We attache our proposal to tests in simulated environment which shows that indeed the stability of wireless network is more sustainable when the perception exists that in its absence.

Routing in mobile Ad-Hoc networks is normally a difficult task, but even more challenging if the network is expected to provide support for audio and video streaming between human-carried devices. Besides normal movement and signal impairment difficulties, those multimedia applications may impose extra end-to-end requirements. The computation of optimized and/or constrained network paths using one or more metric restrictions is called QoS (Quality-of-Service) routing. This paper presents QMRS, a QoS routing protocol for Ad-Hoc networks which aims to support applications with QoS requirements including requirements for the end-to-end delay. This protocol proposes a on-demand multiple routes discovery mechanism that is able to find up to three node-disjoint paths that meet the QoS requirement. Additionally, and for the purpose of guarantee the stability of the routing process, it uses the signal strength of the links between neighbouring nodes to elect the most stable route. Such route will be used as the primary choice to forward traffic. The other discovered routes will be maintained as backup in order to eventually replace the primary route, in case of disruption or degradation of required QoS.

QMRS was implemented in NS-3 and evaluated in comparison with AODV and AMR (an AOMDV-like protocol). Simulation results show significant improvements, with respect to the average end-to-end delay, packet delivery ratio and throughput.

Energy consumption is one of the most fundamental constraints in wireless sensor network (WSN) design. While data transmission is usually the most energy consuming event, minimizing the transmit power under the condition of satisfying the required packet transmission quality would be an important and effective strategy for reducing energy consumption. In this paper, a novel Adaptive Transmit Power Adjustment technique (ATPA) for ZigBee network under Wi-Fi interference is proposed and implemented in the Crossbow MICAz motes of our testbed. The proposed ATPA technique dynamically and rapidly adapts to the varying interference from the collocated wireless local area network (WLAN) and selects optimal transmit power level that not only decreases the energy consumption of packet transmissions, but also maintains the required packet loss rate (PLR). The effectiveness of ATPA has been validated through the comprehensive performance evaluation experiments conducted on our testbed.

Cognitive radio networks need to operate in a wide range of frequencies. This requirement brings up new challenges that do not exist in other wireless networks. Switching from a certain frequency to another frequency incurs a non-negligible cost in cognitive radio networks and depends on the wideness between the previous and current frequencies. This cost is especially important in ad hoc cognitive radio networks when the cognitive devices have a single transceiver. Research studies related to green networks indicate the need for methods that address energy consumption in cognitive radio networks. In this paper, we analyze the impact of the channel switching cost in terms of energy consumption. We formulate an optimization problem that makes frequency and time slot allocation to the cognitive devices in an ad hoc cognitive radio network so that the energy cost related to frequency switching is minimized. We formulate our optimization problem as an integer linear program and comparatively evaluate the energy cost of varying switching energy consumption with constant switching energy consumption. Our simulation results indicate that taking into account the different energy consumption while switching to different frequency bands is vital for resource allocation in cognitive radio networks with a single transceiver.

High mobility of vehicles, limited transmission range of roadside units (RSUs), and channel status (busy or idle) cause dynamic topological changes in Vehicular Networks (VNs). Due to these dynamic topological changes, maintaining full connectivity arises as a main communication challenge in VNs. Moreover, the high number of channel switching also effects the quality of network connectivity causing an another significant problem in VNs. In order to overcome these challenges, we analyze the full connectivity provisioning in VNs by proposing four cognitive channel selection algorithms, parameterizing the vehicle satisfaction ratio and the number of channel switching. Specifically, the proposed channel selection algorithms provide minimal channel switching ratio while conserving full network connectivity. We also compare the results of multi-channel selection and single channel selection and simulation results show that network connectivity can be enhanced while optimizing the channel switching with our proposed cognitive channel selection algorithms.

The use of mobility in a Wireless Sensor Network has already been indicated as a feature whose exploitation would increase the performances and the ease of mantainance in these environments. Expecially in a event-based WSN, where is necessary a prompt response in terms of data processing and offloading, a set of mobile flying sinks could be a good option for the role of autonomous data collectors. For those reasons in this paper we propose a distributed algorithm to independently and autonomously drive a mobile sink through the nodes of a WSN and we show its preferability over more classical routing approaches expecially in the presence of a localized generation of large amount of information. Our result shows that, in the case of fairly complete coverage of the area where the nodes lie, it is possible to promptly notify a mobile sink about the presence of data to offload, drive it to the interested area and achieve interesting performances.

In this paper, a so-called LMAT (Localization algorithm with a Mobile Anchor node based on Trilateration) path planning algorithm is being validated using simulations and evaluated in experiments using a real unmanned aerial vehicle (UAV). Our focus is to find out if the flying path used for our unique scenario, represented by a disastrous event, fulfills the required accuracy. In our scenario, we consider an UAV that moves around buildings and localizes “survived” devices inside a building. This can help to detect victims and to accelerate the rescue process. For this, fast and accurate localization is essential.

In Wireless Rechargeable Sensor Networks, one or more special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes, using wireless power transfer technology. In this paper, we present some state of the art algorithms that apply to characteristic problems in such networks, namely efficient use of wireless power transfer using i) one Mobile Charger, ii) multiple Mobile Chargers, iii) collaborative mobile charging.

Estimating the maximum stress through stress distribution of a structure is an important indicator for structural safety evaluation. Structural health monitoring can be used to do this with a variety of measuring equipment such as strain gage, LVDT, LDS. All the measuring equipment, however, has some weakness in the configuration of complex wire network and some inconvenience of replacing faulty sensors. Therefore, this paper suggests a technique that can estimate stress distribution of steel beam structure under uncertain load and support conditions by using motion capture system (MCS). MCS is a Vision-based Monitoring System, which measures 3D coordinates of multiple markers attached to the surface of steel beam without installing the complex wire network. In this study, the stress distribution is estimated from an analytic model by using displacement values measured by MCS. For the evaluation of the estimated stress distribution, comparing with the measured stress from ESG is performed.

In recent years, developments in construction technology have resulted in structures increasing in both size and height, with related safety concerns also increasing. These structures may pose significant risks in scenarios where they suffer significant damage, for example, from external shock or the influence of aging. This paper proposes a wireless sensor structural health monitoring (SHM) system construction and operation method for the verification of structural safety and risk determination in real time. The method first selects the sensor location and type via a simulation of the response of the structure for the construction of the SHM system. The system wirelessly receives the data from the data acquisition system used to collect the data from the sensors attached to the structure. Empirical results obtained by applying the proposed system to the monitoring of the concrete wall of a liquefied natural gas (LNG) tank and measuring the response of the structure confirm the feasibility of our proposed method.

Power consumption is an important goal for many applications, expecially when the power can be wasted doing nothing. Video surveillance is one of this application where the camera can be on for long period without “see” nothing. For this reason several power management techniques were carried out in order to reduce the activities of the camera when it is not needed. In this work we focus on surveillance applications performed through Video Surveillance Camera (VSC) that are not permanently active, but need to be properly “woken-up”, by specific ultra Low Power wireless Sensor Nodes (LPSN) able to monitor continuously the area. named. The LPSN are equipped by Piezoelectric “Passive” Infrared (PIR) sensors to detect the movement, thus they have a specific transmission range (to wirelessly send the “wake-up” messages to the camera sensor device) and a sensing range to detect events of interest (i.e. a man that crosses a specific area). Different deployments may highly impact not only in terms of events detectable, but also in terms of the number of VDS that can be woken-up. In this work, we propose a neural/genetic algorithm, that tries to compute the best deployment of the LPSN, based on two weight factors that “prioritize” the first objective, that is the number of VSC that can be woken-up or the second objective, namely the events detectable. The two objectives can be opposite and based on the different values assigned to the weight factors, different deployments can be obtained. The performance evaluation is realized through a simulation tool and we will show the effectiveness of our approach to reach very effective deployments in different scenarios.

The scope of this paper is to present a low-overhead localized algorithm for the target coverage problem in wireless sensor networks. The algorithm divides the sensors into active and sleep mode nodes in order to conserve energy and extend the network lifetime. The set of active mode nodes provide full coverage to a set of targets (points) in the field. The decision of which sensors will remain active at any time is locally taken by the nodes by exchanging messages with each other. This kind of messages add overhead in the network, while high overhead can dramatically decrease the network lifetime especially in case of high node density environments. To tackle this problem we propose two variations of a localized algorithm with low communication complexity. Finally, the operational effectiveness of the proposed approaches is evaluated through simulation, while their superiority against other relevant proposed solutions in the literature is illustrated. The results show a great improvement in terms of communication cost while achieving an adequate network lifetime.

Connectivity restoration after a node failure is one of the major issues in wireless ad-hoc networks. In particular, failures can lead to a network partitioning and a huge loss of information. Therefore, a fast mechanism is needed to heal the network between the partitions. In this paper, we consider the scenario where an intermediate node failures and a mobile system is moving autonomously to restore connectivity and provide the best service. We propose a fast connectivity restoration algorithm that is based only on local information. We implement our solution on a real robotic platform and we present some experimental results using a simple case scenario.