Non-cooperative Networks Research Articles

Noncooperative Topology Inference of Wireless Networks With Monitoring Sensors

With the widespread application of wireless networks, the importance of intelligent analysis of network behaviors is becoming increasingly prominent. In the analysis of networks behaviors, learning and reasoning about the connectivity of unknown networks is a fundamental problem. To obtain the topology information of a non-cooperative wireless network that could not be accessed by the monitoring sensors, we propose a topology inference algorithm based on the network two-dimensional spatio-temporal features (TDSTF). Specifically, the monitoring sensor network monitors the power of the non-cooperative network and locates the nodes of the non-cooperative network exploiting the neural network (NN)-based method. Then, the communication time and distance between the non-cooperative nodes are used as characteristics to infer the topology of the non-cooperative network based on K-Nearest Neighbors (KNN). Simulation results validate that the proposed TDSTF topology inference algorithm outperforms other topology inference algorithms that do not consider both spatial and temporal features and can greatly improve the inference accuracy.

Designing weighted and directed networks under complementarities

Strategic complementarities influence various social and economic activities. This study introduces a model to design a weighted and directed complementarity network to achieve a planner's objectives. The network represents the direction and intensity of complementarities between agents, influencing their best-responses to one another and determining equilibrium efforts. The planner's objective function can be convex, as commonly assumed in prior research, or arbitrarily concave to represent scenarios with diminishing marginal returns to each agent's effort. In all scenarios, optimal networks are generalized nested split graphs (GNSGs) which exhibit a link-dominance hierarchy among agents. These optimal networks are often strictly hierarchical, leading to inequality between ex ante identical agents. Additional analysis of a non-cooperative network formation game reveals that all decentralized equilibrium networks are inefficient GNSGs.

ДОСЛІДЖЕННЯ ТОЧНОСТІ ЛОКАЛІЗАЦІЇ В СЕНСОРНИХ МЕРЕЖАХ ПРИ ЗАСТОСУВАННІ МЕТОДУ МУЛЬТИЛАТЕРАЦІЇ

One of the main tasks of deploying sensor networks is determining the coordinates of nodes that are unknown at their initial placement. This problem is known as the localization problem of sensor networks. It can be solved if each node has a GPS receiver in its composition. However, such nodes are more expensive, and for networks of various purposes, for example, environmental monitoring, fixation of moving objects in a certain area, various types of IoT, and others, nodes without GPS can be used. To solve the problem of localization in such networks, so-called anchor nodes are used, the coordinates of which are known. They form a certain percentage of the total number of nodes. They are used to find the coordinates of the remaining nodes that are part of the network. If only anchor nodes are used for the localization problem, then such networks are called non-cooperative networks. If all nodes participate in the positioning of nodes, then such networks are called cooperative. Different methods are used to solve this problem such as the method of trilateration, multilateration, triangulation, random, and others. To apply these methods, it is necessary to know the distances or angles to nodes whose coordinates are determined based on the nodes with known coordinates. At the same time, various methods are used to determine distances, namely: TDOA, DOA, TOA, RTT, RSSI. Corresponding means in modern nodes are present as separate functions. For example, the IEEE 802.15.4 (ZigBee) standard. In this paper, studies of the influence of the multilateration method on the accuracy of determining the coordinates of nodes were carried out. An algorithm was used, according to which the position of the node, for which the coordinates should be determined, was generated, as well as the coordinates of the anchor nodes that take part in the localization of the node. The distance measurement error according to the ZigBee standard with a range of 1000 m was taken as 10 %. The number of anchor nodes was changed throughout the analysis, and the respective positioning error was calculated. For greater statistical significance, the experiments were repeated a certain number of times while changing the initial value of the generator of uniformly distributed random numbers, and at the same time, the average value of the localization error, and the minimum and maximum values were calculated. The obtained statistical data were visualized in the form of relevant graphs. As a result of research, it was determined that six anchor nodes are enough to obtain a positioning accuracy of 10 m.

Safety DV-hop positioning algorithm of underwater acoustic sensor networks based on Nesterov accelerated gradient descent method

Before sensing and transmitting data, the underwater nodes need to calculate and estimate their location information through anchor nodes with known locations. The ranging-free positioning algorithm DV-hop can be applied to the underwater wireless sensor network in a relatively poor environment, which is not required high positioning accuracy. However, some anchor nodes may be destroyed and utilized to deter unknown nodes’ precise positioning in the underwater confrontation scenario. Therefore, we propose a computationally efficient algorithm for determining the location of sensor nodes in harsh and confrontational underwater environments and resisting non-cooperative network attacks. This algorithm integrates Nesterov accelerated gradient descent (NAG) into the DV-hop positioning algorithm and prunes the data by selecting the measurement inconsistency to get better positioning accuracy and higher security. The simulation experiment confirms that our proposed algorithm has better measurement accuracy in the underwater environment than the existing algorithms.

HeteroTiC: A robust network flow watermarking based on heterogeneous time channels

Tracking back stealthy attackers is still a great challenge in face of complicated Internet environments and increased attacker capabilities. As a possible solution, network flow watermarking has been developed to embed attack labels actively in data flows, trying to identify the attack source accurately in time. However, due to the influences of uncertain network noises, the robustness of watermarking cannot be ensured efficiently in case of non-cooperative network scenarios currently. Meanwhile, it is difficult to enhance robustness and covertness simultaneously when suffering from severe network noises. Thus, a robust network flow watermarking based on Heterogeneous Time Channels (HeteroTiC) is proposed, for which packet order, packet timing and packet size constitute heterogeneous time channels to carry watermarks. The beginning positions are located by packet order to support accurate synchronization, the long watermark sequences are carried by inter-packet delays to improve capabilities against packet dropping and time jitter, the mapping relationships for the watermark sequences on heterogeneous time channels are mixed by packet size of the flow itself to enhance covertness. With multiple layers design of watermarking, HeteroTiC is designed to accomplish fast detection and accurate extraction on watermarks. By experiments, the average detection accuracy reaches 100% and the average extraction accuracy is validated with 94.2%. Furthermore, the same mapping pattern on multiple flows only accounts for 8.11%, which validates the covertness against multiple flow similarities. The extraction accuracy exceeds 9.76%∼18.1% in comparison with classical watermarking methods, which validates the robustness under network noises in Internet.

Development of a Bounded Two-Stage Data Envelopment Analysis Model in the Intuitionistic Fuzzy Environment

Data Envelopment Analysis is a powerful tool for evaluating the efficiency of decision-making units for the purpose of ranking, comparing, and differentiating efficient and inefficient units. Classical Data Envelopment Analysis methods operate by measuring the efficiency of each DMU compared to similar units without considering their internal workings and structures, which make them unsuitable for cases where DMUs are multistaged processes with intermediate products or when inputs and outputs are ambiguous or nonconfigurable. In problems that involve uncertainty, intuitionistic fuzzy sets can offer a better representation and interpretation of information than classic sets. In this paper, the noncooperative network data envelopment analysis model of Liang et al. (2008), which is based on Stackelberg game theory and efficiency decomposition, is expanded using the concepts of best and worst relative returns Data Envelopment Analysis model of Azizi et al. (2013) into an interval efficiency estimation model with α-β cuts for two-stage DMUs with trapezoidal intuitionistic fuzzy data. Furthermore, the method of Yue (2011) is used to rank these DMUs in terms of their intuitionistic fuzzy interval efficiency. A numerical example is also provided to illustrate the application of the proposed bounded two-stage intuitionistic Data Envelopment Analysis model.

An Equilibrium Analysis of a Secondary Mobile Data-Share Market

Internet service providers are offering shared data plans where multiple users may buy and sell their overage data in a secondary market managed by the ISP. We propose a game-theoretic approach to a software-defined network for modeling this wireless data exchange market: a fully connected, non-cooperative network. We identify and define the rules for the underlying progressive second price (PSP) auction for the respective network and market structure. We allow for a single degree of statistical freedom—the reserve price—and show that the secondary data exchange market allows for greater flexibility in the acquisition decision making of mechanism design. We have designed a framework to optimize the strategy space using the elasticity of supply and demand. Wireless users are modeled as a distribution of buyers and sellers with normal incentives. Our derivation of a buyer-response strategy for wireless users based on second price market dynamics leads us to prove the existence of a balanced pricing scheme. We examine shifts in the market price function and prove that our network upholds the desired properties for optimization with respect to software-defined networks and prove the existence of a Nash equilibrium in the overlying non-cooperative game.

Hybrid Precoding in Cooperative Millimeter Wave Networks

In this paper, we study the performance of cooperative millimeter wave (mmWave) networks with hybrid precoding architectures. Considering joint transmissions and BS silence strategy, we propose hybrid precoding algorithms which minimize the sum power consumption of the base stations (BSs), for both fully- and partially-connected hybrid precoding (FHP and PHP, respectively) schemes, for single-carrier and orthogonal frequency-division multiplexing systems. We reformulate the analog precoding part as an equal-gain transmission problem, which only depends on the channel information, and the digital precoding part as a relaxed convex semidefinite program subject to per-user quality-of-service constraints that gives the optimal sum power consumption in terms of the BS silence strategy. In order to reduce the complexity of the hybrid precoding algorithm with optimal BS silence strategy, we propose a sub-optimal hybrid precoding algorithm that iteratively put BSs with small power into the silent mode. The simulation results show that, depending on the parameter settings, the power consumption of the PHP may be dominated by the RF transmit power and it may result in a larger power consumption than the FHP. For the cases with 2 BSs and 4 users, implementation of the FHP and the PHP in cooperative networks reduces the required RF transmit power, compared to the case in a non-cooperative network, by 71% and 56%, respectively.

On Nash Equilibria in Non-Cooperative All-Optical Networks

We consider the problem of determining a routing in all-optical networks, in which some couples of nodes want to communicate. In particular, we study this problem from the point of view of a network provider that has to design suitable payment functions for non-cooperative agents, corresponding to the couples of nodes wishing to communicate. The network provider aims at inducing stable routings (i.e., routings corresponding to Nash equilibria) using a low number of wavelengths. We consider three different kinds of local knowledge that agents may exploit to compute their payments, leading to three corresponding information levels. Under complete information, the network provider can design a payment function, inducing the agents to reach a Nash equilibrium mirroring any desired routing. If the price to an agent is computed only as a function of the wavelengths used along connecting paths (minimal level) or edges (intermediate level), the most reasonable functions either do not admit Nash equilibria or admit very inefficient ones, i.e., with the largest possible price of anarchy. However, by suitably restricting the network topology, a constant price of anarchy for chains and rings and a logarithmic one for trees can be obtained under the minimal and intermediate levels, respectively.

Movable Platform-Based Topology Detection for a Geographic Routing Wireless Sensor Network.

With the increasing adoption of the Internet-of-Things (IoT), the wireless sensors network (WSN), as an underlying application of IoT, has attracted increasing attention. Topology, the working structure used to observe WSN, is the most instinctive form in troubleshooting and has great significance to WSN management and safety. To this end, it is imperative to recover WSN topology for the purpose of network management and non-cooperative network detection. Traditional network topology recovery mainly relies on the monitoring modules installed in nodes, or an extra network attached. However, these two approaches have several limitations, such as high energy consumption for monitoring nodes, time synchronization problems, reuse failure, limitation to specific targeted networks and high cost. In this paper, we present a new approach to recover the topology of WSN that adopts location-based routing protocols, based on movable platforms. Our observation is that the network topology is consistent with the node routing, as the nodes choose the next hop according to the geological position of neighbor nodes. Hence, we calculate the cost parameters of choosing routing nodes for the targeted network according to the partial connection of the nodes. Based on those cost parameters, we can determine the topology of the whole network. More specifically, by collecting the geological position and data packets of the nodes from movable platforms, we are able to infer the topology of the WSN according to the recovered partial connection of nodes. Our approach can be easily adopted to many scenarios, especially for non-cooperative large-scale networks. The evaluation of 30 simulations shows that the accuracy of recovery is above 90%.

Clustering of unknown protocol messages based on format comparison

As a solution to detect and analyse unknown or proprietary protocols, Protocol Reverse Engineering(PRE) has been developed swiftly in recent years. In this field, message clustering aimed at protocol format serves as a fundamental solution for differentiating of unknown protocol messages. This paper works on the problem of format-oriented message clustering of unknown protocols, including messages from proprietary or non-cooperative network environments with their specifications unknown. By introducing basic rules of ABNF, we define Token Format Distance (TFD) and Message Format Distance (MFD) to represent format similarity of tokens and messages, and introduce Jaccard Distance and an optimized sequence alignment algorithm (MFD measurement) to compute them. Then, a distance matrix is built by MFD and we feed it to DBSCAN algorithm to cluster unknown protocol messages into classes with different formats. In this process, we design an unsupervised clustering strategy with Silhouette Coefficient and Dunn Index applied to parameter selecting of DBSCAN. In experiment on two datasets, the harmonic average v-measures of homogeneity and completeness on result clusters are both above 0.91, with fmis and coverages no less than 0.97. Together with iqr of v-measure and fmi bellow 0.1 and 0.03 separately in boxplot analyses, this method is proved to have remarkable validity and stability. Comprehensive analyses and comparisons on these indexes also show considerable advantages of our method over previous work.

Hub Network Design in a Cooperative Environment

As an important strategic decision, the design of the hub network directly affects the transportation efficiency and costs of the entire network. Sharing resources to reduce costs through cooperation is the future development of logistics and transportation networks. From the perspective of horizontal cooperation, this paper focuses on the hub location problem of two carriers sharing hub facilities in a cooperative environment. A mixed-integer programming model with minimum total network cost in a cooperative environment is constructed. Numerical examples demonstrate that the supplementary cost due to cooperation will affect the result of cooperation. When the supplementary cost is within a specific range, the cooperative network is more cost-effective than non-cooperative networks.

Investigation of multiple hop cooperative communication system over time-selective Nakagami-m fading channel

Real-time communication is affected by practical constraints such as node mobility and imperfect channel state information. Most technical contributions in the area of cooperative communication neglect these practical constraints, thus, assumes ideal propagation scenarios. Such approximations make sense in low-rate systems, but can lead to very false results when examining future high data rate systems. In this work, closed-form expression of pairwise error probability (PEP) is derived for dual hop and multiple hop selective decode-and-forward relaying network over time-selective Nakagami-m fading links. Space–time block code is used in combination with multiple-input multiple-output to achieve the diversity gain along with cooperative diversity. To obtain the optimal source-relay power allocation factors, a mathematical framework has been proposed to improve the performance of the system in the power-constraint situation. Simulation results have been presented for various values of fading severity parameter and channel variance. Results for different node-mobility scenarios are also provided. Results show that the system performance improves by increasing the fading severity parameter and relay-to-destination (RD) channel gain. It is noted that the relaying network’s diversity order (DO) is the same as the non-cooperative network’s DO in a scenario when both source node (SN) and destination nodes (DNs) are static, and relay node (RN) is mobile. Also, if the RN and DN are static and the SN is mobile, DO will be equivalent to zero. At high signal-to-noise ratio (SNR), system performance with equal and optimal energy distribution can be seen approaching an asymptotic floor limit, because system performance independent of the power of the noise components. The effect of mobility of the DN on the average per-block PEP output is less important compared to the mobility of the SN. The scheme is restricted by an asymptotic error floor with a greater SNR regime for other node-mobility situations. The analytical results are verified by Monte Carlo simulations for M-ary signaling maximal ratio combiner cooperative system.

Supply-Demand Matching in Non-Cooperative Social Networks

Supply-Demand Matching in Non-Cooperative Social Networks

Optimal European cooperative supply chains for carbon capture, transport, and sequestration with costs share policies

AbstractIn the past decades, CO2 constituted nearly the 80% of anthropogenic greenhouse gases emissions therefore, global actions are needed to tackle the increase of carbon concentration in the atmosphere. CO2 (carbon) capture and storage has been highlighted among the most promising options to decarbonize the energy and industry sectors. Considering a large‐scale infrastructure at European level, economic cooperation has been highlighted as a key requirement to relieve single countries from too high risk and commitment. This article proposes an economic optimization for cooperative supply chains for CO2 capture and storage, by adopting policies that balance the spread of costs among countries, according to local characteristics in terms of population, CO2 emissions, and macroeconomic outcome. Results show that the additional European investment for cooperation (max. +2.6% with respect to a noncooperative network) should not constitute a barrier toward the installation and operation of such more effective network designs.

A non-cooperative model of network formation with endogenous link strength.

Interaction among multiple agents to exchange resources or information is interpreted as network interaction in the field of social sciences. The strategic formation of these network links has been formalized both as cooperative and noncooperative games. This paper analyses the formation of such non-cooperative networks where agents have the discretion to choose as well as decide the level of investment in their connections. This study specifically analyses the case of two-way flow networks where the link between any two agents can be formed and maintained by only one of them whereas the benefit from this link accrues to both the agents. Unlike previous studies, this framework relaxes the assumption of investment decision for an agent to be independent of their partners' level of investment. Also, agents are assumed to have a constraint on the amount of resources that they can allocate across links. In the baseline model, the link strength takes the form of a concave function of individual investments, and agents prefer the most reliable path that maximizes the product of link strengths. Using Nash equilibrium as the stability and aggregate benefit maximizing as the efficiency concept, we show that both the stable and efficient networks are a unique type of flower network. Further, by generalizing the value of paths connecting agents, other networks are also found to be emerging as stable but the efficient architecture still takes the form of the same flower type network, in line with the base model.

Dynamic power splitting scheme for DF relaying‐based SWIPT networks with direct link

A dynamic power splitting (DPS) scheme for decode-and-forward (DF) relaying based simultaneous wireless information and power transfer (SWIPT) networks with a direct link (DL) is considered. The optimal DPS factor can maximise the received signal-to-noise ratio at the destination node. If the DPS factor is equal to zero, the proposed model will degenerate into a non-cooperative network which only utilises the DL to accomplish the transmission. The authors first derive the optimal DPS factor, and then derive analytical expressions for outage probability and ergodic capacity. Moreover, to obtain the diversity order, the asymptotic expression for outage probability is also derived. Numerical results show that the performance of the proposed scheme is the best compared to the other competitive schemes, especially in terms of the ergodic capacity.

Optimal Complementarity Networks

We study the problem of a planner designing a weighted and directed network to achieve her objectives subject to an organizational resource constraint. The network determines the complementarities between agents and, hence, their equilibrium effort. The planner's objective function can be convex to capture efficiency objectives or strictly concave to capture egalitarian concerns. We show that all optimal networks are generalized nested split graphs (GNSGs) that exhibit a `link-dominance' ordering among agents. The concept of GNSGs generalizes the previous notion of a nested split graph defined among unweighted and undirected networks to weighted and directed networks. Under a wide range of conditions, optimal networks must be hierarchical so that some agent is more influential and exerts strictly higher effort than others. This situation occurs even if agents are ex ante identical and the planner has egalitarian concerns. In a noncooperative network formation game, we show that all decentralized equilibrium networks are inefficient GNSGs.

Delay–Accuracy Tradeoff in Opportunistic Time-of-Arrival Localization

While designing a positioning network, the localization performance is traditionally the main concern. However, collection of measurements together with channel access methods require a nonzero time, causing a delay experienced by network nodes. This fact is usually neglected in the positioning-related literature. In terms of the delay-accuracy tradeoff, broadcast schemes have an advantage over unicast, provided nodes can be properly synchronized. In this letter, we analyze the delay-accuracy tradeoff for localization schemes in which the position estimates are obtained based on broadcasted ranging signals. We find that for dense networks, the tradeoff is the same for cooperative and noncooperative networks, and cannot exceed a certain threshold value.

Cooperative Source Node Tracking in Non-Line-of-Sight Environments

The accuracy of localization is highly degraded in indoor and harsh environments where source nodes either do not have connections with a sufficient number of anchor nodes due to strong attenuation or have very poor range estimates due to NLOS propagation. Cooperative localization is a technique in which the source nodes communicate not only with the anchor nodes, but also with each other. Hence, the source nodes can collect several additional measurements which significantly improve the localization performance. Although many studies have examined NLOS-degraded localization of a static node in noncooperative networks, and many others have examined the impact of cooperation for static localization, there is no work which considers cooperative tracking of mobile nodes. To address this open problem, in this work, we examine cooperative tracking, particularly in NLOS environments. More specifically, we develop a novel sensor tracking algorithm based on semidefinite programming (SDP) which has the ability to mitigate NLOS propagation. Our simulations show that the new SDP-based tracking algorithm outperforms the classic extended Kalman filter as well as the other recently proposed algorithms for noncooperative tracking in NLOS environments. We also show that the algorithm can be extended to cooperative networks, and that a substantial performance benefit is realized by cooperation.