Wireless rechargeable sensor networks (WRSNs) have overcome the energy limitation bottleneck through wireless power transfer (WPT) technology. Traditional research has primarily focused on enhancing charging efficiency, while the critical issue of location privacy security arising from wireless charging has received scant attention. Additionally, sensors are vulnerable to detection and harm by malicious attackers, posing a significant threat to network integrity. In this paper, we propose two attack schemes, termed Least Squares Method (LSM) attack model and Centroid Method (CM) attack model for compromising sensor location privacy by exploiting charging power information and mobile charger behaviors. To counter such threats, we develop a scheme aimed at maximizing the node location privacy protection capabilities of the network. We propose a theoretical analysis to exploit the features of the proposed scheme. Finally, extensive test-bed experiments and simulations have been conducted to validate the effectiveness of our algorithms. The results demonstrate that our algorithms can protect at least 78% of the nodes without significantly compromising their survival rate.

In this paper we introduce a new, minimum-cuts based spanner algorithm, when the goal is twofold: (a) to decrease the number of active links in the network and (b) to maintain the ability of the SDN (Software-Defined Networking) controller to perform load balancing. The proposed spanner concept also can be used in order to reduce the running time of the SDN centralized routing algorithm . In addition, we show how to maintain the spanner under dynamic link insertion, deletion and changed weight. The validation of our solution is made through the analysis and simulation that show the superiority of our approach in many cases.

Known Visual Encryption Scheme (VES) schemes encode the secret image pixels into n subpixel maps (shares) of size $m \times m$, where m is a parameter of the scheme. The pixel encoding is based on some pixel visual property, for example transparency. The resulting pixel maps contain black and white pixels and look like random collection of black and white pixels, such that it is impossible to reconstruct the original pixel. To reconstruct the original secret image, at least k out of n shares must be stacked together, where k is the scheme parameter. The reconstructed image appears grey, with varying shades of darker and lighter pixels. In this work, we introduce an optical VES solution that utilizes a physical model of wave interference. The image reconstructed using the proposed VES consists of pure black and white pixels, while maintaining the computational efficiency of traditional VES methods. An additional advantage of the proposed VES scheme is its enhanced security model. Besides being perfectly information-theoretic secure against honest and curious adversaries, it is also resilient against active, Byzantine adversaries. The proposed VES can be utilized in Flying Adhoc Networks, where a swarm of Unmanned Aerial Vehicles collaborates to search for a target based on a pre-assigned secret image.

In this paper, we consider the problem of prediction of Radio Link Failures (RLF) in flying ad hoc networks (FANETs).Many environmental factors that influence the quality of radio wave propagation are dynamic, and thus, drones must continually learn and update their radio link quality prediction model while they operate online.Online machine learning algorithms can be used to build adaptive RLF predictors without requiring a pre-deployment effort.To predict the RLF, we use an online machine learning algorithm and information gathering by message-passing from the neighbors.We propose an algorithm called ML-Net (Machine Learning and Network algorithm) to predict RLF.To the best of our knowledge, the combination of online machine learning algorithms together with the message-passing algorithm has not been used before.The proposed methodology outperforms the state-of-the-art online machine learning algorithms.

Vehicular ad hoc network (VANET) is an emerging technology with a promising future and great challenges. It aims to promote safe driving, improve traffic flow and also enables a variety of entertainment applications. A fundamental need in such a network is the ability to assess vehicular speed. This enables the collection of statistics for the purpose of traffic engineering and long-term planning, and is also critical information for law enforcement groups. Many existing speed assessment technologies suffer from high physical visibility, and relatively expensive hardware. Even those that avoid detection, are inflexible due to being location specific. Therefore, reducing the ability to track and enforce traffic speed and limiting the collection of statistics for traffic engineering. In this paper, we propose a method for vehicle speed assessment, by extracting an induced Communication Connectivity Graph (CCG) from VANET optimized link state routing (OLSR) protocol, and composing an optimization problem for assessing the speed boundaries, using graph hop distance based constraints. We performed evaluation experiments in different traffic scenarios using traffic simulation tool. Our method can provide a cost-effective, easy to implement and hard to uncover solution for vehicles speed assessment on highways.

The objective of our work is to address the challenge of delivering time-sensitive data across a multi-hop wireless network. We aim to maximize the number of packets that reach their destination before the strict deadline. To achieve this, we introduce a deep reinforcement learning (DRL) approach that determines the optimal route, scheduling, and power allocation for each flow while complying with strict time constraints.

In this work, we study the connected version of the covering problem motivated by the coverage of ad-hoc drones’ swarm. We focus on the situation where the number of drones is given, and this number is not necessarily enough to cover all users. That is, we deal with a budget optimization problem, where the budget is the number of given drones. We assume that each ground user has different QoS requirements. Additionally, each ground user has a weight that corresponds to the importance (rank) of the user. Moreover, we consider the case when there is no third-party entity that provides connectivity to the drones. In this paper, we propose a 3D deployment scheme with the given number of drones such that the sum of the weights (ranks) of the ground users covered by drones is maximized (when the covering radii satisfy QoS of these users), and the drones form a connected graph. We present a number of approximate solutions with provable guaranteed performance evaluation that have been validated also through the simulation platform.

LEO constellations create a network that includes the satellites (as routing nodes) connected by Inter-Satellite Links, and the satellite terminals dynamically connected to one or more satellites. The combination of transient, high-rate changes with high latency presents a unique challenge for designing a routing protocol that can provide guaranteed bandwidth, and support the frequent changes without packet drops. Current works focus on end-to-end routing between multiple gateways and terminals and do not provide guaranteed service.This paper addresses the problem of routing traffic from a source terminal to a destination terminal on a LEO constellation using Asymmetric Differential Routing (ADR) to plan ’semi-fixed’ routes. ADR keeps most of the planned route fixed and only minor (differential) adjustments are required to account for handovers.

In this study, we consider a scenario where Unmanned Aerial Vehicles are deployed in an area of interest in order to monitor this area, and the data gathering process following the monitoring is applied towards a central UAV (sink) for analysis. Our objective is to find a minimum-length TDMA schedule by jointly determining the scheduled concurrent links at each slot, along with their used power levels and the established routes toward the sink, under SINR requirements. Since the problem is known to be NP-hard, we aim to provide solutions to real-world situations using efficient heuristic approach. Our research goal is to use deep neural network to approximate the solution of finding the minimum frame length for the TDMA frame. We propose the TDMA frame length minimization by the deep neural network approach (named MTFLet). We have performed extensive experimental evaluations of MTFLet and simulations showing that MTFLet outperforms other state-of-art methods.

A low earth orbit (LEO) observation satellite offers a shorter distance to the target area, low cost, and low communication latency. The low orbit translates to high orbital speed and results in short observation and communication contact periods. Swarms of multiple satellites offer extended coverage and spatial resolution for applications such as earth observation and monitoring. LEO communication satellite constellations create a network that includes hundreds to tens of thousands of satellites with onboard processing capabilities (as routing nodes) connected by Inter-Satellite Links (ISL) that provide continuous coverage of the earth. The LEO constellations aim to provide end-to-end routing between multiple gateways and terminals. This paper assumes the LEO constellation satellite payload includes sensors and processing capabilities. We explore the problem of managing an autonomous LEO virtual satellite swarm that will provide continuous and adjustable coverage. We preset a novel virtual swarm: a subset of the constellation satellites is dynamically assigned to the swarm when they cover the target area. The virtual swarm algorithm provides distributed data synchronization among the swarm virtual satellites and a distributed dynamic assignment of physical satellites to the virtual swarm satellites.

Collaborative secure image matching is a problem that is applicable in various domains, for both – data in rest and data in motion. The problem is defined as follows. There is a secret image, and a set of n mobile agents. The set of mobile agents should match (compare) an observed image to the original secret image. In this paper we discuss some of the existing approaches, and present an alternative solution applied and analyzed for different applications. The first application is a swarm of Unmanned Aerial Vehicles (UAV) that search for a target specified by an image. The second application is a social network that serves as a smart storage device capable of performing distributed, secret image matching operations. Our solution is based on the well-known Visual Encryption Scheme (VES) and projections of visual bit maps rather than (quadratic complexity) messages exchange in implementing Secure Multi Party Computation (MPC) scheme. We present a perfect-information-theoretic secure solution for this problem. To keep the original image secrecy, at least k out of n mobile agents are required to retrieve any information about the original image.

The social Internet of Things (IoT) (SIoT) helps to enable an autonomous interaction between the two architectures that have already been established: social networks and the IoT. SIoT also integrates the concepts of social networking and IoT into collaborative edge computing (CEC), the so-called CEC-based SIoT architecture. In closer proximity, IoT devices self-organize into a CEC-based SIoT computing cluster and provide social device-to-device (S-D2D) services, such as computation offloading, service discovery, and content delivery. In the CEC-based SIoT, however, cooperation based on social connections leads to a problem calledsocial and spatial physical trade-off. This problem is also referred to as themismatchproblem, which arises because the spatial neighbors in the social layer cannot always be related. The spatial distance thus calls for additional multi-hop transmissions. This work presents a novel solution called 3-D-social identifier structure(3-D-SIS)model. The 3-D-SIS model is based on 3-D social space (3-D-SS) and considers social ties and physical connections (i.e., intra-neighbor) of the SIoT devices and utilizes a 3-D structure to evaluate that relationship. Moreover, it minimizes the end-to-end delay and communication cost to address the mismatch problem. To validate the performance of the(3-D-SIS)model, we use the real traces of social networks(INFOCOM06). The results show that the 3-D-SIS selects the best neighbor in S-D2D communication and improves performance in terms of end-to-end delay and throughput.

The publication of user data for statistical analysis and research can be extremely beneficial for both academic and commercial uses, such as statistical research and recommendation systems. To maintain user privacy when such a publication occurs many databases employ anonymization techniques, either on the query results or the data itself. In this article, we examine and analyze the privacy offered when using the query-set-size control method for aggregate queries over a data structures representing various topologies. We focus on the mathematical queries of minimum, maximum, median, and average and show some query types that may be used to extract hidden information. We prove some combinations of these queries will maintain a measurable level of privacy even when using multiple queries. We offer a privacy probability measure, indicating the probability of an attacker to obtain information defined as sensitive by utilizing legitimate queries over such a system. Our results are mathematically proven and backed by simulations using vehicular network data based on the TAPASCologne project.

In this paper, an unmanned aerial vehicles (UAVs) deployment framework based on machine learning is studied.It aims to maximize the sum of the weights of the ground users covered by UAVs while UAVs forming a connected communication graph.We focus on the case where the number of UAVs is not necessarily enough to cover all ground users.We develop an UAV Deployment Deep Neural network (UD-DNNet) as a UAV's deployment deep network method.Simulation results demonstrate that UDDNNet can serve as a computationally inexpensive replacement for traditionally expensive optimization algorithms in real-time tasks and outperform the state-of-the-art traditional algorithms.

As of 2018, several low orbit (LEO) constellations are being designed and planned. These include SpaceX, OneWeb, LeoSat, Telesat and lately Amazon Kuiper. Some of these constellations include Inter-Satellite Links (ISL) communication at the initial or second phase as well as on-board processing capabilities. The LEO constellations create a network that includes the satellites (as routing nodes) connected by ISLs, and the satellite terminals that dynamically connect to one or more satellites. The LEO network presents unique challenges to traffic routing and service planning due to dynamic changes in the network topology (interconnection between satellites, and between satellites and terminals). In addition, the LEO latency (which is low, compared to GEO and MEO) is significant when using legacy routing protocols (The constellation end-to-end latency can be in the order of 100 mSecs and ground-to-satellite latency is in the order of 10 mSecs).This paper addresses the problem of sending traffic from a source terminal to a destination terminal connected through multiple satellites while guaranteeing and enabling planning of the service metrics/QoS (bandwidth and latency) and handling satellite handovers.

A global service LEO constellation aims to provide service to any terminal covered by the constellation planes. To reduce the satellite cost, which is directly related to its power usage and weight, each satellite should be able to service (cover) all the terminals within its Field-of-View (FoV) using the satellites beams in the most efficient way. LEO satellite network vendors use different approaches to handle the user terminals diverse locations. A stepping (or tracking) beam constellation provides service to predefined areas instead of a full coverage. As a result, satellites using stepping beams are more efficient, as power is used only for populated areas. When the constellation shifts, beams are allocated such that each area is serviced by one of the satellites that has the area in its FoV. Stepping beams constellations raise unique and complicated tasks. When admitting a new service area, we should verify it can be covered by a satellite beam at any coverage combination of the moving constellation. The algorithms should take into account the satellite limitations (power, number of beams).Previous works analyzed the overall efficiency of each constellation architecture and the technologies of the on-board beams, while little attention was paid to the algorithm that validates a consistent coverage of new service areas. The major contribution of this paper is a novel algorithm for validating new service areas in a LEO stepping beam constellation.

As of 2018, several low orbit (LEO) constellations are being designed and planned. These include SpaceX, OneWeb, LeoSat, Telesat and others. Some of these constellations include Inter-Satellite Links (ISL) communication at the initial or second phase as well as on-board processing capabilities. The LEO constellations create a network that includes the satellites (as routing nodes) connected by ISLs, and the satellite terminals that dynamically connect to one of the satellites. The LEO network presents unique challenges to traffic routing and service planning due to dynamic changes in the network topology (interconnection between satellites, and between satellites and terminals). In addition, the LEO latency (which is low, compared to GEO and MEO) is significant when using legacy routing protocols (each ISL latency can be in the order of 10 mSecs or more and ground to satellite latency is in the order of 10 mSecs). In case of a polar constellation, the LEO satellite orbit is south-to-north on one half of the constellation and north-to-south on the other half. As a result, there are neighboring planes in which satellites are moving in opposite directions. Satellites can easily establish and maintain ISLs with neighboring satellites on the same plane. However, a link with a neighboring satellite on the adjacent plane can only be established if the satellite on that plane is moving in the same direction. The barriers between the two satellite groups are called seams. This paper is the first to analyze the impact of the seam on location based routing in a polar constellation. We propose an asymmetric seam-aware location-based routing algorithm, and use a random walk on a geographical shortest path lattice for load balancing.

IP Networks serve a variety of connected network entities (NEs) such as personal computers, servers, mobile devices, virtual machines, hosted containers, etc. The growth in the number of NEs and technical considerations has led to a reality where a single IP address is used by multiple NEs. A typical example is a home router using Network Address Translation (NAT). In organizations and cloud environments, a single IP can be used by multiple virtual machines or containers running on a single device. Discovering the number of NEs served by an IP address and clustering their traffic correctly is of value in many use cases for security, lawful interception, asset management, and other purposes. In this paper, we introduce IPvest, a system that incorporates unsupervised and supervised learning algorithms based on various features for counting and clustering network traffic of NEs masqueraded by a single IP. The features are based on the characteristics of operating systems (OSs), NAT behavior, and users' habits. Our model is evaluated on real-world datasets including Windows, Linux-based, Android, and iOS-based devices, containers, virtual machines, and load-balancers. We show that IPvest can count the number of NEs and cluster their traffic with high precision, even for containers running on a single device and servers behind a load-balancer.

We examine the problem of discovering the set P of points in a given topology which constitutes a k-median set for that topology, while maintaining location privacy. That is, there exists a set U of points in a d-dimensional topology for which a k-median set must be found by some algorithm A, without disclosing the location of points in U to the executor of A. We define a privacy preserving data model for a coordinate system we call a “Topology Descriptor Grid”, and show how it can be used to find the rectilinear 1-median of the system and a constant factor approximation for the Euclidean 1-median. Additionally, we achieve a constant factor approximation for the rectilinear 2-median of a grid topology.

In this paper, we study the problem of data gathering in ad-hoc sensor networks using a mobile entity called mule. The mule traverses the children of failed sensors, to prevent loss of data. Our objective is to define the optimal communication tree and the mule's placement such that the mule's overall traveling distance is minimized. We explore this problem in several network topologies including: unit disc graph on a line (UDL), general unit disc graph (UDG), and a complete graph with failing probabilities on the nodes (CGFP). We provide an optimal solution for the UDL problem and two approximation algorithms for the UDG problem. For the CGFP problem we outline the two possible structures of an optimal solution and provide near optimal approximation algorithms.

IN OUR talk we will focus on networks with no predefined infrastructure (ad-hoc networks, sensor networks, vehicular networks). There are many optimization problems derived from the context of such networks including power assignment mechanisms, scheduling, data gathering, etc. We will discuss various techniques tacking these problems emphasizing the importance of mobile nodes locations and its influence on the tightness of the solutions.

Many small businesses and public areas offer free Wi-Fi access, but may wish to restrict network access only to their customers or patrons inside the physical property. Unfortunately, due to the nature of wireless networks, this is difficult to accomplish. We develop and implement CLAC, a Crowdsourced Location aware Access Control scheme using physical layer information to address this challenge. It crowdsources both channel state information (CSI) and received signal strength (RSS) of already validated users to classify future users. We propose and use two CSI metrics in CLAC: CSI Cross-Antenna Stability Metric and CSI Cross-Frame Stability Metric, which summarize well the spatial and temporal CSI characteristics respectively. CLAC is evaluated in an office and a classroom. Evaluation results show that CLAC performs well in both environments, allowing most valid users inside the area to access the network, while the chance that invalid users outside the boundary may access the network is small.

Wireless communication systems, such as RFIDs and wireless sensor networks, are increasingly being used in security-sensitive applications, e.g. credit card transactions or monitoring patient health in hospitals. Wireless jamming by transmitting artificial noise, which is traditionally used as an offensive technique for disrupting communication, has recently been explored as a means of protecting sensitive communication from eavesdroppers.

Security-sensitive applications, such as patient health monitoring and credit card transactions, are increasingly utilizing wireless communication systems, RFIDs, wireless sensor networks, and other wireless communication systems. The use of interference-emitting jammers to protect these sensitive communications has been recently explored in the literature, and has shown high potential. In this paper we consider optimization problems relating to the temporal distributions of jammers' activity, and the suitable coding regimes used for communication. Solving the joint problem optimally enables comprehensive security in space, at a low power consumption and low communication overhead. The joint optimization of jamming in space and time is driven by a new framework that uses the bit-error probability as a measure of communication quality. Under this framework, we show how to guarantee information-theoretic security within a geographic region, and with increased flexibility to tailor the coding regime to the problem's geometry. We present efficient algorithms for different settings, and provide simulations for various scenarios using the bit-error probability functions. These simulations demonstrate the efficiency of the scheme. We believe that our scheme can lead to practical, economical and scalable solutions for providing another layer of protection of sensitive data, in cases where encryption schemes are limited or impractical.

Modern vehicles are configured to exchange warning messages through IEEE 1609 Dedicated Short Range Communication (DSRC) over IEEE 802.11p Wireless Access in Vehicular Environment (WAVE). Essentially, these warning messages must associate an authentication factor such that the verifier authenticates the message origin via visual binding. Interestingly, the existing vehicle communication incorporates the message forward-ability as a requested feature for numerous applications. On the contrary, the vehicle security infrastructure is vulnerable to message forwarding i.e., Messages seem to originate from a malicious vehicle (due to non-detectable message relaying) instead of the actual message sender. We introduce the non forward-able authentication to avoid an adversary coalition attack scenario. These messages should be identifiable with respect to the immediate sender at every hop. We propose to utilize immediate optical response verification in association with the authenticated key exchange over radio channel. These optical responses are generated through hardware means, i.e., A certified Physically Unclonable Function (PUF) device embedded on the front and rear of the vehicle.

In this paper, we study the problem of efficient data recovery using the data mules approach, where a set of mobile sensors with advanced mobility capabilities re-acquire lost data by visiting the neighbors of failed sensors, thereby improving network resiliency. Our approach involves defining the optimal communication graph and mules' placements such that the overall traveling time and distance is minimized regardless to which sensors crashed. We explore this problem under different practical network topologies such as general graphs, grids and random linear networks and provide approximation algorithms based on multiple combinatorial techniques. Simulation experiments demonstrate that our algorithms outperform various competitive solutions for different network models, and that they are applicable for practical scenarios.

Mobile ad hoc networks (MANETs) are networks that are created on the fly (ad hoc) between various mobile nodes and do not require infrastructure. The mobile nodes can move around, and the network would automatically reconfigure itself to allow connectivity. Vehicular ad hoc networks (VANETs) are a subclass of MANETs that is expected to have a key role in the intelligent transportation systems of the future. VANETs provide vehicle-to-vehicle and vehicle-to-roadside communication in order to support safety and comfort applications. Despite being a subclass of MANETs, VANETs have fundamentally different behavior. This paper presents a scheme consisting of a media access control protocol and a clustering algorithm designed to reduce interferences in VANETs. Our scheme, which is intended for safety applications in highway environments, employs dynamic multihop clustering, allows better utilization of network resources, and improves network performance.

We study a facility location problem motivated by requirements pertaining to the distribution of charging stations for electric vehicles: Place a minimum number of battery charging stations at a subset of nodes of a network, so that battery-powered electric vehicles will be able to move between destinations using "t-spanning" routes, of lengths within a factor t > 1 of the length of a shortest path, while having sufficient charging stations along the way. We give constant-factor approximation algorithms for minimizing the number of charging stations, subject to the t-spanning constraint. We study two versions of the problem, one in which the stations are required to support a single ride (to a single destination), and one in which the stations are to support multiple rides through a sequence of destinations, where the destinations are revealed one at a time.

In this paper we consider the problem of efficient data gathering in sensor networks for arbitrary sensor node deployments. The efficiency of the solution is measured by a number of criteria: total energy consumption, total transport capacity, latency and quality of the transmissions. We present a number of different constructions with various tradeoffs between aforementioned parameters. We provide theoretical performance analysis for our approaches, present their distributed implementation and discuss the different aspects of using each. We show that in many cases our output-sensitive approximation solution performs better than the currently known best results for sensor networks. Our simulation results validate the theoretical findings.

In the near future, vehicles will establish a spontaneous connection over a wireless radio channel, coordinating actions and information. Security infrastructure is most important in such a hazardous scope of vehicles communication for coordinating actions and avoiding accidents on the roads. One of the first security issues that need to be established is authentication. Vehicle authentication with visual binding prior to establishing a wireless radio channel of communication is useful only when the vehicles possess unique visual attributes. These vehicle static attributes (e.g., Licence number, brand and color) are certified together with the vehicle public key. Therefore, we consider the case of multiple malicious vehicles with identical visual static attributes. Apparently, dynamic attributes (e.g., Location and direction) can uniquely define a vehicle and can be utilized to resolve the true identity of vehicles. However, unlike static attributes, dynamic attributes cannot be signed by a trusted authority beforehand. We propose an approach to verify the coupling between non-certified dynamic attributes and certified static attributes on an auxiliary communication channel, for example, a modulated laser beam. Furthermore, we illustrate that the proposed approach can be used to facilitate the usage of existing authentication protocols such as NAXOS, in the new scope of ad-hoc vehicle networks.

In this paper we consider the extension of the betweenness centrality measure which is used in social and computer communication networks to estimate the potential monitoring and control capabilities a node may have on data flowing in the network. Unlike the standard betweenness centrality measure which takes into account only the shortest paths between the nodes of given network, our, so-called Δ-betweenness centrality measure is based on short paths between the nodes. We present an efficient algorithm for computing this measure and show experimental results supporting the importance of newly defined measure.

In this paper, we consider a set of n mobile wireless nodes, which have no information about each other. The only information a single node holds is its current location and future mobility plan. We develop a two-phase distributed self-stabilizing scheme for producing a bounded hop-diameter communication graph. In the first phase, nodes construct a temporary underlying topology and disseminate their current location and mobility plans. This is followed by a second phase, in which nodes construct the desired topology under two modes: static and dynamic. The static mode provides a fixed topology which does not change in spite of node movements; the dynamic mode allows the topology to change; however, the hop-diameter remains the same. We provide an O(λ,λ2)-bicriteria approximation (in terms of total energy consumption and network lifetime, respectively) algorithm in the static mode: for an input parameter λ, we construct a static h-bounded hop communication graph, where h=n/λ + log λ. In the dynamic mode, given a parameter h, we construct an optimal (in terms of network lifetime) h-bounded hop communication graph when every node moves with constant speed in a single direction along a straight line during each time interval. Our results are validated through extensive simulations.

We study the problem of spanner construction in wireless ad-hoc networks through power assignments under two spanner models—distance and energy. In particular, we are interested in asymmetric power assignments so that the induced communication graph holds good distance and energy stretch factors simultaneously. In addition, we consider the following optimization objectives: low total energy consumption, low interference level, low hopdiameter, and high network lifetime. Two node deployment scenarios are studied: random and deterministic. For n random nodes distributed uniformly and independently in a unit square, we present several power assignments with varying construction-time complexities. The results are based on various geometric properties of random points and shortest path tree constructions. Due to the probabilistic nature of this scenario, the probability of our results converges to one as the number of network nodes, n , increases. For the deterministic case, we present two power assignments with nontrivial bounds. These are established in addition to shortcut edges that satisfy desired threshold stretch. To the best of our knowledge, these are the first results for spanner construction in wireless ad-hoc networks with provable bounds for both energy and distance metrics simultaneously. Our power assignments, in addition, try optimizing additional network properties, such as network lifetime, interference, and hop diameter.

In this paper, we study strategies for allocating and managing friendly jammers, so as to create virtual barriers that would prevent hostile eavesdroppers from tapping sensitive wireless communication. Our scheme precludes the use of any encryption technique. Applications include domains such as (i) protecting the privacy of storage locations where RFID tags are used for item identification, (ii) secure reading of RFID tags embedded in credit cards, (iii) protecting data transmitted through wireless networks, sensor networks, etc. By carefully managing jammers to produce noise, we show how to reduce the SINR of eavesdroppers to below a threshold for successful reception, without jeopardizing network performance.

Current network processors (NPs) increasingly deal with packets with heterogeneous processing times. In such an environment, packets that require many processing cycles delay low-latency traffic because the common approach in today's NPs is to employ run-to-completion processing. These difficulties have led to the emergence of the Multipass NP architecture, where after a processing cycle ends, all processed packets are recycled into the buffer and recompete for processing resources. In this paper, we provide a model that captures many of the characteristics of this architecture, and we consider several scheduling and buffer management algorithms that are specially designed to optimize the performance of multipass network processors. In particular, we provide analytical guarantees for the throughput performance of our algorithms. We further conduct a comprehensive simulation study, which validates our results.

We consider a geometric optimization problem that arises in network design. Given a set P of n points in the plane, source and destination points s,t ∈ P, and an integer k > 0, one has to locate k Steiner points, such that the length of the longest edge of a bottleneck path between s and t is minimized. In this paper, we present an O(n log2 n)-time algorithm that computes an optimal solution, for any constant k. This problem was previously studied by Hou et al. [Hou10], who gave an O(n2log n)-time algorithm. We also study the dual version of the problem, where a value λ > 0 is given (instead of k), and the goal is to locate as few Steiner points as possible, so that the length of the longest edge of a bottleneck path between s and t is at most λ.

Current network processors (NPs) increasingly deal with packets with heterogeneous processing times. As a consequence, packets that require many processing cycles can significantly delay low-latency traffic, because the common approach in today's NPs is to employ run-to-completion processing. These difficulties have led to the emergence of the Multipass NP architecture, where after a processing cycle ends, all processed packets are recycled into the buffer and re-compete for processing resources. In this work we provide a model that captures many of the characteristics of this architecture, and consider several scheduling and buffer management algorithms that are specially designed to optimize the performance of multipass network processors. In particular, we provide analytical guarantees for the throughput performance of our algorithms. We further conduct a comprehensive simulation study that validates our results.

This paper studies the problem of interference-free broadcast in wireless ad hoc networks. In particular, we are interested in asymmetric power assignments so that the induced broadcast communication graph is both, energy efficient and has a short collision-free broadcast schedule. We consider both random and deterministic node layouts and develop four different broadcast schemes with provable performance guarantees on three optimization objectives simultaneously: total energy consumption, network lifetime and collision-free schedule length. We also show some numerical results which support our findings.

This paper studies the problem of topology control in random wireless ad-hoc networks through power assignment for n nodes uniformly distributed in a unit square. In particular, we are interested in asymmetric power assignments so that the induced communication graph has a good distance and energy stretch simultaneously, with additional optimization objectives: both minimizing the total energy consumption, interference level, hop-diameter, and maximizing the network lifetime. We present several power assignments with varying construction time complexity. The probability of our results converges to one as the number of network nodes, n, increases. To the best of our knowledge, these are the first results for spanner construction in wireless ad-hoc networks with provable bounds for both, energy and distance, metrics simultaneously.

In this paper, we study asymmetric power assignments that induce a low-energy k-strongly connected communication graph with spanner properties. We address two spanner models: energy and distance. The former serves as an indicator for the energy consumed in a message propagation between two nodes, while the latter reflects the geographic properties of routing in the induced communication graph. We consider a random wireless ad hoc network with IVI = n nodes distributed uniformly and independently in a unit square. For k ∈ {1, 2}, we propose several power assignments that obtain a good bicriteria approximation on the total cost and stretch factor under the two models. For k > 2, we analyze a power assignment developed by Carmi et al. and derive some interesting bounds on the stretch factor for both models as well. We also describe how to compute all the power assignments distributively, and we provide simulation results. To the best of our knowledge, these are the first provable theoretical bounds for low-cost spanners in wireless ad hoc networks.

Abstract Wirelessad hocnetworks are characterized by several performance metrics, such asbandwidth, transport, delay, power, etc. These networks are examined by constructing a tree network. A core node is usually chosen to be themedianorcenterof the multicast tree network with a tendency to minimize a performance metric, such as delay or transport. In this paper, we present a new efficient strategy for constructing and maintaining a core node in a multicast tree for wirelessad hocnetworks undergoing dynamic changes, based on local information. The new core (centdian) function is defined by a convex combination signifying total transport and delay metrics. We provide two bounds ofO(d) andO(d+l) time for maintaining the centdian using local updates, wherelis the hop count between the new center and the new centdian, anddis the diameter of the tree network. We also show anO(n log n) time solution for finding the centdian in the Euclidian complete network. Finally, an extensive simulation for the construction algorithm and the maintenance algorithm is presented along with an interesting observation. Copyright © 2009 John Wiley & Sons, Ltd.

This paper studies asymmetric power assignments for which the induced communication graph is a good spanner of the Euclidean graph, induced on the wireless nodes V, while the total energy is minimized. We propose two spanner models: distance and energy. We consider a random wireless ad-hoc network with |V| = n nodes distributed uniformly and independently in a unit square. For the first model, we propose an approximation algorithm, which constructs a power assignment so that the induced network is an O ((1 + alpha)(n-m)/m log n + alpha)-spanner of Gvwith high probability, such that the total energy is at most betaldrm+2 times the optimum, for any alpha > 1, beta ges 1 + 2/(alpha-1), and any positive integer m les n in O(mn2) time. For the second model, we develop a power assignment such that the resulting network is a 2-spanner with a total energy of at most O(log n) times the optimum in O(n4log n) time. We also analyze a power assignment developed and show it is a low cost good k-fault resistant spanner. To the best of our knowledge, these are the first provable theoretic results for low cost spanners in wireless ad-hoc networks.

We introduce the use of movement-signals (analogously to flight signals and bees waggle) as a mean to transfer messages, enabling the use of distributed algorithms among the robots. We propose one-to-one deterministic movement protocols that implement explicit communication.

The buffered crossbar switch architecture has recently gained considerable research attention. In such a switch, besides normal input and output queues, a small buffer is associated with each crosspoint. Due to the introduction of crossbar buffers, output and input contention is eliminated, and the scheduling process is greatly simplified. We analyze the performance of switch policies by means of competitive analysis, where a uniform guarantee is provided for all traffic patterns. We assume that each packet has an intrinsic value designating its priority and the goal of the switch policy is to maximize the weighted throughput of the switch. We consider FIFO queueing buffering policies, which are deployed by the majority of today's Internet routers. In packet-mode scheduling, a packet is divided into a number of unit length cells and the scheduling policy is constrained to schedule all the cells contiguously, which removes reassembly overhead and improves Quality-of-Service (QoS). For the case of variable length packets with uniform value density (Best Effort model), where the packet value is proportional to its size, we present a packet-mode greedy switch policy that is 7-competitive. For the case of unit size packets with variable values (Differentiated Services model), we propose a preemptive greedy switch policy that achieves a competitive ratio of 21. As far as we know, this is the first constant-competitive FIFO policy for this architecture in the case of variable value packets. The presented policies are simple and thus can be efficiently implemented at high speeds. Moreover, our results hold for any value of the internal switch fabric speedup.

Wireless sensor networks represent a new generation of real time traffic communications and high data rate sensor applications such as structural health monitoring and control. In this work we study some problems of data gathering in sensor networks. The information that the sensor collect about their environment must be delivered in timely fashion to collecting central processing system. We prove in this research that finding the optimal schedule in order to minimize the maximal delivery time with restrictions on the total idle time allowed in a general network topology with a single designated destination base station is NP-hard. We also refer to a special case of linear network topology for which we present several optimization algorithms: First we present an algorithm to minimize the number of tardy messages. We then present an algorithm to minimize the maximal lateness. Finally, we present an algorithm to minimize the maximal completion time. All of the scheduling optimization algorithms.

This article addresses a real-life problem - obtaining communication links between multiple base stations sites, by positioning a minimal set of fixed-access relay antenna sites on a given terrain. Reducing the number of relay antenna sites is considered critical due to substantial installation and maintenance costs. Despite the potential significant cost saving by eliminating even a single antenna site, a hardly optimal manual approach is employed due to the computation complexity of the problem. We suggest several alternative automated heuristics, relying on terrain preprocessing to find educated potential points for positioning relay stations. A large-scale experiment was conducted showing that the saving potential increases when more BSs are required to be interconnected and in any case is better than the one obtained by ah uman expert.

We consider a game that models the creation of a wireless ad hoc network, where nodes are owned by selfish agents. We study a novel cost sharing model in which agents may pay for the transmission power of the other nodes. Each agent has to satisfy some connectivity requirement in the final network and the goal is to minimize its payment with no regard to the overall system performance. We analyze two fundamental connectivity games, namely broadcast and convergecast. We study pure Nash equilibria and quantify the degradation in the network performance called the price of anarchy resulting from selfish behavior. We derive asymptotically tight bounds on the price of anarchy for these games. We also study centralized network design. One of the most important problems in wireless ad hoc networks is the minimum-energy broadcast. Recently, there appeared many new applications such as real-time multimedia, battlefield communications and rescue operations that impose stringent end-to-end latency requirement on the broadcasting time. However, the existing algorithms that minimize the broadcasting energy tend to produce solutions with high latency. We consider the problem of bounded-hop broadcast. We present approximation algorithms for this problem.

Several routing schemes in ad hoc networks first establish a virtual backbone and then route messages via backbone nodes. One common way of constructing such a backbone is based on the construction of a connected dominating set (CDS). In this article we present a very simple distributed algorithm for computing a small CDS. Our algorithm has an approximation factor of at most 6.91, improving upon the previous best-known approximation factor of 8 due to Wan et al. [2002]. The improvement relies on a refined analysis of the relationship between the size of a maximal independent set and a minimum CDS in a unit disk graph. This subresult also implies improved approximation factors for many existing algorithm.

Trees of special properties are required to provide efficient network management of group communications in mobile ad hoc networks. Usually, such trees try to balance between the requirements to minimize the total tree cost and the requirement to minimize the maximal shortest path. This work presents a novel solution for efficient multicast trees that fulfill both requirements called SPLAST. The following discussion covers the development process, starting from centralized static solution, through distributed implementation to a complete distributed algorithm that cope with various scenarios that are relevant to wireless ad hoc networks by efficient management and maintenance of the underlying components of the algorithm. Simulation inquiry shows that the average performance of SPLAST is attractive as well.

Abstract Thep‐center problem is to locatepfacilities on a network so as to minimize the largest distance from a demand point to its nearest facility. Thep‐median problem is to locatepfacilities on a network so as to minimize the average distance from a demand point to its closest facility. We consider these problems when the network can be modeled by an interval or circular‐arc graph whose edges have unit lengths. We provide, given the interval model of annvertex interval graph, anO(n) time algorithm for the 1‐median problem on the interval graph. We also show how to solve thep‐median problem, for arbitraryp, on an interval graph inO(pnlogn) time and on a circular‐arc graph inO(pn2logn) time. We introduce a spring representation of the objective function and show how to solve thep‐center problem on a circular‐arc graph inO(pn) time, assuming that the arc endpoints are sorted. © 2002 Wiley Periodicals, Inc.

A downhole-to-surface communication channel consisting of a long vertical cylinder (the stem) and an isolated downhole in-line cylinder (the electrode) embedded in a homogeneous Earth is considered in this work. A signal voltage is applied between the electrode and stem, and the received voltage is picked up at the surface between the stem and a ground point or between two ground points. The analysis includes consideration of conductor longitudinal and surface impedance, joint resistance, voltage source resistance, and Earth propagation effects to provide a realistic model for assessing the performance of the communication channel for measurement-while-drilling, drill stem testing, and production testing in oil and gas industry applications. Simulation results indicate that consideration of all of these effects is imperative for satisfactory modeling.