Connectivity Guarantees Research Articles

Controlling the spread of infectious diseases by using random walk method to remove many important links

Understanding the network structure is critical for controlling and mitigating the spread of infectious diseases. Removing many important links to control the spread of infectious diseases is often more convenient and cost-saving than isolating individuals. Therefore, we develop an algorithm (RW) for identifying important links based on random walks in complex networks. With the guarantee of network connectivity, removing many important links from the network can better reduce the largest eigenvalue of the adjacency matrix, thus increasing the epidemic threshold and reducing the fraction of infected individuals, and further effectively controlling the spread of infectious diseases. In order to verify the effectiveness and scalability of our algorithm, we conducted many experiments on top of a large number of real-world networks and synthesis networks to compare with some classical algorithms. The results show that our algorithm can effectively identify important links to control the spread of infectious diseases in social networks.

Critical nodes identification: A non-cooperative method for unknown topology information in ad hoc networks

The foundation of ad hoc networks lies in the guarantee of continuous connectivity. However, critical nodes, whose failure can easily destroy network connectivity, will influence the ad hoc network connectivity significantly. To protect the network efficiently, critical nodes should be identified accurately and rapidly. Unlike existing critical node identification methods for unknown topology that identify critical nodes according to historical information, this paper develops a critical node identification method to relax the prior topology information condition about critical nodes. Specifically, we first deduce a theorem about the minimum communication range for a node through the number of nodes and deployment ranges, and prove the universality of the theorem in a realistic two-dimensional scenario. After that, we analyze the relationship between communication range and degree value for each node and prove that the greater number of nodes within the communication range of a node, the greater degree value of nodes with high probability. Moreover, we develop a novel strategy to improve the accuracy of critical node identification without topology information. Finally, simulation results indicate the proposed strategy can achieve high accuracy and low redundancy while ensuring low time consumption in the scenarios with unknown topology information in ad hoc networks.

Deep-Reinforcement-Learning-Based Multitarget Coverage With Connectivity Guaranteed

Deriving a distributed, time-efficient, and connectivity-guaranteed coverage policy in multitarget environment poses huge challenges for a multirobot team with limited coverage and limited communication. In particular, the robot team needs to cover multiple targets while preserving connectivity. In this article, a novel deep-reinforcement-learning-based approach is proposed to take both multitarget coverage and connectivity preservation into account simultaneously, which consists of four parts: a hierarchical observation attention representation, an interaction attention representation, a two-stage policy learning, and a connectivity-guaranteed policy filtering. The hierarchical observation attention representation is designed for each robot to extract the latent features of the relations from its neighboring robots and the targets. To promote the cooperation behavior among the robots, the interaction attention representation is designed for each robot to aggregate information from its neighboring robots. Moreover, to speed up the training process and improve the performance of the learned policy, the two-stage policy learning is presented using two reward functions based on algebraic connectivity and coverage rate. Furthermore, the learned policy is filtered to strictly guarantee the connectivity based on a model of connectivity maintenance. Finally, the effectiveness of the proposed method is validated by numerous simulations. Besides, our method is further deployed to an experimental platform based on quadrotor unmanned aerial vehicles and omnidirectional vehicles. The experiments illustrate the practicability of the proposed method.

Connectivity Guarantee Within UAV Cluster: A Graph Coalition Formation Game Approach

Unmanned Aerial Vehicle (UAV) clustering is promising for performing large-scale missions because of high mobility and easy deployment. However, the connectivity problems caused by the high mobility of UAVs and the interferences are mostly ignored in existing UAV mission executions. Rapid restoration of UAV network connectivity is essential for preventing communication disruption and improving the overall network performance. Thus, a graph coalition formation game that integrates the UAV time-varying topology graph with the coalition formation game is proposed to rapidly restore the connectivity of the UAV network in need. The method improves the utility of UAV clustering and ensures the network connectivity. Then, a graph coalition formation game algorithm based on the shortest path tree (SPT-GCF) rapidly forms an approximately optimal coalition structure. The simulation results show that the proposed approach increases the average utility of UAV clustering by 6.5% and 14.5% respectively when compared with the existing non-overlapping coalition formation game (NOCFG) and the coalition formation game without considering the cluster connectivity.

Hybrid Algorithm for Node Deployment with the Guarantee of Connectivity in Wireless Sensor Networks

In this paper, the problem of deployment in wireless sensor networks is investigated. The authors propose a Hybrid Modified Crow Search Bee Algorithm (HMCSBA) for coverage maximization with the guarantee of connectivity between the deployed sensors. Firstly, a Modified Crow Search Algorithm (MCSA) is proposed based on the basic CSA algorithm to form a connected network after initial random deployment. The position equation of the original CSA was updated by introducing a linear flight length that increases throughout iterations to force the sensors to join the network. Then, the Bees Algorithm (BA) is applied to optimize the network coverage without losing connectivity between the deployed sensors. Simulations and comparative studies were carried out to prove the relevance of the proposed algorithm. Results demonstrate that the proposed algorithm can optimize the coverage and guarantee network connectivity.

Construction of an ecological security pattern based on functional wetland theory: A case study in a landscape city

The high-intensity development of a city encroaches on the ecological land, such as lakes, rivers, and forests, which changes the stable land relationship, resulting in ecological security problems, such as regional waterlogging and a decline in biodiversity. Identifying urban ecological systems and constructing ecological security patterns (ESP) are of great importance for urban ecological protection and spatial planning. The complexity of the ecological environment in landscape cities makes them more difficult for planning and construction than in plain cities. Additionally, they are more susceptible to torrential rains, mountain torrents, and river tides in the process of urbanization. This study introduced the functional wetland theory into the construction of the ESP and obtained a new set of methods for landscape cities. Based on the functional wetland theory, the “patch-corridor-matrix” model was used to combine the geographic information system (GIS) runoff and catchment analysis with the MSPA-MCR ecological corridor construction method to form a new wetland and habitat network by coupling the two together. Additionally, construction principles of protection priority, maximization of ecological benefits, guarantee of connectivity, and targeted design to guide the construction of landscape cities were put forward. This study takes the central urban area of Fuzhou as an example to show the application path of this method.

An Efficient Message Dissemination Scheme for Minimizing Delivery Delay in Delay Tolerant Networks

Delay tolerant networks (DTNs) are a kind of sparse and highly mobile wireless networks, where no stable connectivity guarantee can be assumed. Most DTN users have several points of interest (PoIs), and they enjoy disseminating messages to the other users of the same PoI through WiFi. In DTNs, some time-sensitive messages (disaster warnings, search notices, etc.) need to be rapidly propagated among specific users or areas. Therefore, finding a path from the source to the destination with the shortest delay is the key problem. Taking the dissemination cost into consideration, we propose an efficient message dissemination strategy for minimizing delivery delay (MDMD) in DTNs, which first defines the user’s activeness according to the transiting habit among different PoIs. Furthermore, depending on the activeness, an optimal user in each PoI is selected to constitute the path with the shortest delay. Finally, the MDMD with inactive state (on the way between PoIs) is further proposed to enhance the applicability. Simulation results show that, compared with other dissemination strategies, MDMD achieves the lowest average delay, and the comparable average hopcounts, on the premise that the delivery ratio is guaranteed to be 100% by the sufficient simulation time.

When Best Effort is Not Good Enough: Incomplete Contracting, Risk Allocation, and Demand for Consumer Protection in the Market for Broadband Access Services

Starting from a luxury available to small networks of relatively high-income users, high-speed access to the open Internet has become a necessity for social and economic participation of individuals, competitiveness of business, and economic development. In the transition of broadband from a luxury to a necessity over the past two decades, “best effort” retail contracts (i.e. up to xMbps, subject to varying network conditions) have provided Internet service providers (ISPs) with significant flexibility in managing scarce capacity in response to growing consumer demand for network resources. Over time however, the emergence of a wide variety of advanced Internet applications that require reliable high-speed connectivity (i.e. minimum effective bandwidth/speed, Quality of Service (QoS) guarantees) has stimulated the development of a wide range of network management technologies that enable the delivery of quality of service guarantees and fine-grained service quality and price differentiation (e.g. across applications, senders, users). The combination of these factors has led to the development of a multi-tiered Internet in which scarce capacity is bifurcated into a basic best effort access path to the open Internet and a luxury class of prioritized/sponsored services on the same physical infrastructure. From an economic perspective, mitigating negative externalities from growth in the “fast lane” on best effort “slow lanes” in this differentiated broadband ecosystem have emerged as a seemingly intractable challenge in countries that are further behind in the transition from legacy copper to next generation fiber/4G broadband technologies. Previous research analyzes the emergence of a two-tiered Internet and draws policy inferences primarily in terms of the existence of market power by monopolistic/duopolistic infrastructure providers, inefficient discrimination by this class of gatekeepers to the open Internet, and/or innovation on the edges of the system. There has been little attention paid to the challenges best effort retail contracts that allocate the risk of capacity under-provisioning pose to buyers in a market where more and more applications require minimum service reliability standards. Voices of consumers are therefore almost always supressed in research and policy debates about the optimal design of institutions for ensuring universal access to the open Internet. This article tries to fill this gap by documenting barriers to accessing the open Internet faced by consumers. The first part of the paper provides an overview of the literature on the implications of imperfect contracting for the efficient operation of market systems and as a driver for consumer protection regulation. Then we use quantitative content analysis/natural language processing (NLP) techniques to analyze over 20,000 consumer complaints and carrier responses submitted to the U.S. Federal Communications Commission (FCC) between 2015 and 2017 obtained through the Freedom of Information Act (FOIA) requests to map the interplay between buyers and sellers in a market for Internet connectivity. We conclude with an analysis of public and private legal mechanisms that may help counteract negative externalities from the rise of a two-tiered Internet on quality and affordability of access to the open Internet.

RTCP: a redundancy aware topology control protocol for wireless sensor networks

Topology control-based sleep-scheduling aims at exploiting node redundancy to save energy and extend the network lifetime, by putting as many nodes as possible in sleep mode, while maintaining a connected network. In this paper, we propose a redundancy aware topology control protocol (RTCP) for a wireless sensor network which exploits the sensor redundancy in the same region. This is achieved by dividing the network into groups so that a connected backbone can be maintained by keeping a necessary set of working nodes and turning off the redundant ones. RTCP allows applications to parameterise the desired connectivity degree. It identifies node redundancy, in terms of communication; it groups redundant nodes together according to their redundancy degrees and threshold of connectivity level. Finally, it schedules nodes in groups for active or sleep mode. The simulation results illustrate that RTCP outperforms some other existing algorithms, in terms of energy conservation, network lifetime and connectivity guarantee.

On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space.

Sensor networks have been used in a rapidly increasing number of applications in many fields. This work generalizes a sensor deployment problem to place a minimum set of wireless sensors at candidate locations in constrained 3D space to k-cover a given set of target objects. By exhausting the combinations of discreteness/continuousness constraints on either sensor locations or target objects, we formulate four classes of sensor deployment problems in 3D space: deploy sensors at Discrete/Continuous Locations (D/CL) to cover Discrete/Continuous Targets (D/CT). We begin with the design of an approximate algorithm for DLDT and then reduce DLCT, CLDT, and CLCT to DLDT by discretizing continuous sensor locations or target objects into a set of divisions without sacrificing sensing precision. Furthermore, we consider a connected version of each problem where the deployed sensors must form a connected network, and design an approximation algorithm to minimize the number of deployed sensors with connectivity guarantee. For performance comparison, we design and implement an optimal solution and a genetic algorithm (GA)-based approach. Extensive simulation results show that the proposed deployment algorithms consistently outperform the GA-based heuristic and achieve a close-to-optimal performance in small-scale problem instances and a significantly superior overall performance than the theoretical upper bound.

Topology control in self-organized optical satellite networks based on minimum weight spanning tree

In this paper, we first propose a distributed minimum spanning tree (DMST) algorithm for optical satellite networks (OSNs). The OSNs are characterized by high dynamic topology, long-distance beam, directional links and supported up to several Gbps data rates. In addition, each satellite node has limited optical transceivers. The problem of constructing a minimum weight spanning tree (MST) in a network is NP-hard due to the transceiver limitation. What makes this problem more challenging is the requirement to deploy the network topology in a distributed scenario, since each node can have only direct information of its neighbors. A fully distributed approximation algorithm is developed, which constructs a spanning tree with approximate minimum average edge weight. We prove that the proposed algorithm can definitely produce a feasible solution. And then, based on the MST constructed by proposed algorithm, we also develop a connectivity guarantee (CG) algorithm to construct a robust topology. The CG algorithm can guarantee the requirement of number of incident links to each node, in order to postpone the performance degradation when a topology variation is taking place. Simulation results show that, compared with existing technologies, the proposed algorithms can achieve better performance with low computational complexity.

A Deadlock-Free and Connectivity-Guaranteed Methodology for Achieving Fault-Tolerance in On-Chip Networks

To improve the reliability of on-chip network based systems, we design a deadlock-free routing technique that is more resilient to component failures and guarantees a higher degree of node connectivity. The routing methodology consists of three key steps. First, we determine the maximal connected subgraph of the faulty network by checking whether the defective components happen to be the cut vertices and bridges of the network topology. A precise fault diagnosis mechanism is used to identify partial defective routers. Second, we construct an acyclic channel dependency graph that breaks all cycles and preserves connectivity of the maximal connected subgraph . This is done through the cycle-breaking and connectivity guaranteed (CBCG) algorithm. Finally, we introduce a fault-tolerant adaptive routing scheme that can be used with or without virtual channels for network congestion avoidance and high-throughput routing. The simulation results show both the effectiveness and robustness of the proposed approach. For an $8 \times 8$ 2D-Mesh with 40 percent of link damage, full connectivity and deadlock freedom are still archived without disabling any faultless router in 98.18 percent of the simulations. In a 2D-Torus, the simulation percentage is even higher (99.93 percent). The hardware overhead for supporting the introduced features is minimal. An on-line implementation of cbcg using TSMC 65nm library has only 0.966 and 1.139 percent area overhead for the $8\times8$ and $16 \times 16$ 2D-Meshes.

Increasing Connectivity in VANETs Using Public Transport Backbones

The Vehicular Ad Hoc Networks (VANETs) can be deployed in several regions of urban environments in different days and times, depending on the flow of vehicles. Because of that, the network behavior concerning topological aspects may vary considerably and the guarantee of connectivity between vehicles is a great challenge. The utilization of a fixed infrastructure can enable the use of VANETs, however, this kind of architecture presents prohibitive costs. In big cities, the metropolitan buses that travel on exclusive lanes may be used to set up a metropolitan vehicular data network (backbone). Therefore, this paper considers the implementation of a live mobile backbone, totally ad hoc (BMVA), which provide infrastructure and increase the network connectivity. In order to demonstrate the viability of the BMVA, statistical analysis were performed based on real data from express buses, which travel on exclusive lanes in the city of Curitiba (PR). Statistical, analytical and simulation results confirm that the buses that travel on exclusive lanes could be used to build a totally ad hoc data network and to provide very good network connectivity. In order to exploit the intrinsic connectivity provided by BMVA a new routing protocol, called P-AODV, is also proposed. The P-AODV aims to give priority to the nodes belonging to BMVA during the route discovery process, thereby improving the network performance.

Deterministic Near-Optimal P2P Streaming

We consider live-streaming over a peer-to-peer network in which peers are allowed to enter or leave the system adversarially and arbitrarily. Previous approaches for streaming have either used randomized distribution graphs or structured trees with randomized maintenance algorithms. Randomized graphs handle peer churn well but have only probabilistic connectivity guarantees, while structured trees have good connectivity but have proven hard to maintain under peer churn. We improve upon both approaches by presenting a novel distribution structure with a deterministic and distributed algorithm for maintenance under peer churn. The algorithm has a constant repair time for connectivity, and near optimal delay. As opposed to order results, the guarantees provided by our algorithm are exact and hold for any network size.

A Group-Based Energy-Saving Algorithm for Sleep/Wake Scheduling and Topology Control in Wireless Sensor Networks

In wireless sensor networks, one of the main design challenges is to save energy of sensors and obtain long system lifetime without sacrificing the quality of network coverage and connectivity. Topology control is the primary technique of energy saving which consists to keep a minimum number of sensor nodes to operate in active mode with the purpose of conserving energy as well as ensuring network connectivity and/or coverage. In this paper, we propose a Group-based Energy-Conserving Protocol (GECP) for wireless sensor networks that extends the network lifetime by sleep scheduling among sensor nodes with the purpose to ensure the network connectivity. It exploits the sensor redundancy in the same region by dividing the network into groups so that a connected backbone can be maintained by keeping only one active node in each group and turning off the redundant ones. The scheduling strategy, used by GECP, minimizes the number of transitions between sleep and active states in order to minimize the transition energy and the leader election frequency. The simulation results confirm the efficiency of GECP in terms of energy conservation, connectivity guarantee and network lifetime.

Cooperative Cloud Service Aware Mobile Internet Coverage Connectivity Guarantee Protocol Based on Sensor Opportunistic Coverage Mechanism

In order to improve the Internet coverage ratio and provide connectivity guarantee, based on sensor opportunistic coverage mechanism and cooperative cloud service, we proposed the coverage connectivity guarantee protocol for mobile Internet. In this scheme, based on the opportunistic covering rules, the network coverage algorithm of high reliability and real-time security was achieved by using the opportunity of sensor nodes and the Internet mobile node. Then, the cloud service business support platform is created based on the Internet application service management capabilities and wireless sensor network communication service capabilities, which is the architecture of the cloud support layer. The cooperative cloud service aware model was proposed. Finally, we proposed the mobile Internet coverage connectivity guarantee protocol. The results of experiments demonstrate that the proposed algorithm has excellent performance, in terms of the security of the Internet and the stability, as well as coverage connectivity ability.

A socially aware routing based on local contact information in delay-tolerant networks.

In delay-tolerant networks, network topology changes dynamically and there is no guarantee of continuous connectivity between any two nodes. These features make DTN routing one of important research issues, and the application of social network metrics has led to the design of recent DTN routing schemes. In this paper, we propose an efficient routing scheme by using a node's local contact history and social network metrics. Each node first chooses a proper relay node based on the closeness to the destination node. A locally computed betweenness centrality is additionally utilized to enhance the routing efficiency. Through intensive simulation, we finally demonstrate that our algorithm performs efficiently compared to the existing epidemic or friendship routing scheme.

Ant colony optimization with greedy migration mechanism for node deployment in wireless sensor networks

Node deployment is one of the most crucial issues in wireless sensor networks because it determines the deployment cost, the detection capability of the networks, and even the network lifetimes. To solve such a problem is an intricate task with realistic deployment factors such as deployment cost, connectivity guarantee, load balancing and channel collisions. In this paper, we consider the problem of grid-based coverage with low-cost and connectivity-guarantee (GCLC), and propose a novel deployment approach, ACO-Greedy, to settle this question. This approach is based on the ant colony optimization with greedy migration mechanism, which can quickly complete the full coverage, and markedly decrease the deployment cost. In addition, ACO-Greedy can dynamically adjust the sensing/communication radius to alleviate the energy hole problem and prolong the network lifetime. The simulation results reveal that our developed approach can not only decrease the deployment cost remarkably, but also effectively balance power consumption among sensor nodes and prolong the network lifetime in grid-based WSNs.

Connectivity guarantees for wireless networks with directional antennas

We study a combinatorial geometric problem related to the design of wireless networks with directional antennas. Specifically, we are interested in necessary and sufficient conditions on such antennas that enable one to build a connected communication network, and in efficient algorithms for building such networks when possible. We formulate the problem by a set P of n points in the plane, indicating the positions of n transceivers. Each point is equipped with an α-degree directional antenna, and one needs to adjust the antennas (represented as wedges), by specifying their directions, so that the resulting (undirected) communication graph G is connected. (Two points p , q ∈ P are connected by an edge in G, if and only if q lies in pʼs wedge and p lies in qʼs wedge.) We prove that if α = 60 ° , then it is always possible to adjust the wedges so that G is connected, and that α ⩾ 60 ° is sometimes necessary to achieve this. Our proof is constructive and yields an O ( n log k ) time algorithm for adjusting the wedges, where k is the size of the convex hull of P . Sometimes it is desirable that the communication graph G contain a Hamiltonian path. By a result of Fekete and Woeginger (1997) [8], if α = 90 ° , then it is always possible to adjust the wedges so that G contains a Hamiltonian path. We give an alternative proof to this, which is interesting, since it produces paths of a different nature than those produced by the construction of Fekete and Woeginger. We also show that for any n and ε > 0 , there exist sets of points such that G cannot contain a Hamiltonian path if α = 90 ° − ε .

MST-based clustering topology control algorithm for wireless sensor networks

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes’ transmission power in two-tiered hierarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy & Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated information to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs’ transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs’ transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node’s degree, average node’s power radius and network lifetime, respectively.