Permissioned blockchains are increasingly being used as a solution to record transactions between companies. Several use cases that leverage permissioned blockchains focus on the representation and management of real-world assets. Since the number of incompatible blockchains is quickly growing, there is an increasing need for a universal mechanism to exchange, or trade, digital assets between these isolated platforms. There currently is no universal mechanism for inter-blockchain asset exchange without a requirement for trusted authorities that coordinate the trade. We address this shortcoming and present XChange, a universal mechanism for asset exchange between permissioned blockchains. To achieve universality and to avoid trusted authorities that coordinate a trade, XChange does not provide atomic guarantees but leverages risk mitigation strategies to reduce value at stake. Our mechanism records the specifications and progression of each trade within records on a distributed log. XChange reduces the economic gains of adversaries by bounding the total amount of fraud they can commit at any time. After having committed fraud, an adversary is forced to finish its ongoing trades before it can engage in new trades. We first present a four-phased protocol that coordinates an asset exchange between two traders. We then outline how trade records can be stored on TrustChain, which is a lightweight distributed ledger specifically built for the tamper-proof storage of data elements. We implement XChange and conduct experiments. Our experiments demonstrate that XChange is capable of reducing the economic gains of adversaries by more than 99.9% when replaying a real-world trading dataset. A deployment on low-resource devices reveals that the latency added to a trade by XChange is only 493 milliseconds. Finally, our scalability evaluation shows that XChange achieves over 1’000 trades per second and that its throughput, in terms of trades per second, scales linearly with the system load.@en

Vertex cover (VC) is one of the most fundamental graph-theoretical problems and has been widely used in wireless sensor networks (WSNs), particularly for the link monitoring problem. It is well known that a solution to the independent set problem (IS), which is another fundamental graph-theoretical problem, is complement of a VC. Self-stabilization is an important concept for designing fault tolerance systems. There have been many self-stabilizing VC and IS algorithms in the field. Even though a self-stabilizing IS algorithm can provide VC solutions, it does not give a theoretical guarantee on approximation ratio. In this work, we focus on practical fault tolerance performance of self-stabilizing IS algorithms in case of a vertex cover problem, particularly link monitoring in WSNs. We implement all existing self-stabilizing VC and IS algorithms and make simulations assuming a WSN in which nodes run synchronously. Results show that self-stabilizing IS algorithms in general are able to find better covers than VC algorithms, as they provide roughly 15% smaller solution sets. Furthermore, IS algorithms that run under distributed scheduler converges to a desired configuration in considerably less number of rounds than VC algorithms.@en

In a multi-agent system where agents provide quantifiable work for each other on a voluntary basis, reputation mechanisms are incorporated to induce cooperation. Hereby agents assign their peers numerical scores based on their reported transaction histories. In such systems, adversaries can launch an attack by creating fake identities called Sybils, who report counterfeit transactions among one another, with the aim of increasing their own scores in the eyes of others. This paper provides new results about the Sybil-proofness of reputation mechanisms. We revisit the impossibility result of Seuken and Parkes (2011), who show that strongly-beneficial Sybil attacks cannot be prevented on reputation mechanisms satisfying three particular requirements. We prove that, under a more rigorous set of definitions of Sybil attack benefit, this result no longer holds. We characterise properties under which reputation mechanisms are susceptible to strongly-beneficial Sybil attacks. Building on our results, we propose a minimal set of requirements for reputation mechanisms to achieve resistance to such attacks, which are stronger than the results by Cheng and Friedman (2005), who show Sybil-proofness of certain asymmetric reputation mechanisms. @en

Web3 is emerging as the new Internet-interaction model that facilitates direct collaboration between strangers without a need for prior trust between network participants and without central authorities. However, one of its shortcomings is the lack of a defense mechanism against the ability of a single user to generate a surplus of identities, known as the Sybil attack. Web3 has a Sybil attack problem because it uses peer sampling to establish connections between users. We evaluate the promising but under-explored direction of Sybil avoidance using network latency measurements, according to which two identities with equal latencies are suspected to be operated from the same node, and thus are likely Sybils. Network latency measurements have two desirable properties: they are only malleable by attackers by adding latency, and they do not require any trust between network participants. Our basic SybilSys mechanism avoids Sybil attackers using only network latency measurements if attackers do not actively exploit their malleability. We present an enhanced version of SybilSys that protects against targeted attacks using a variant of the flow correlation attack, which we name TrafficJamTrigger. We show how the message flows of Round-Trip Time measurements can be used to expose attack patterns and we propose and evaluate six classifiers to recognize these patterns. Our experiments show, through both emulation and real-world deployment, that enhanced SybilSys can serve a fundamental role for Web3, effectively establishing connections to real users even in the face of networks consisting of 99% Sybils.@en

Web3 networks are emerging to replace centrally-governed networking infrastructure. The integrity of the shared public infrastructure of Web3 networks is guaranteed through data sharing between nodes. However, due to the unstructured and highly partitioned nature of Web3 networks, data sharing between nodes in different partitions is a challenging task. In this paper we present the TSRP mechanism, which approaches the data sharing problem through nodes auditing each other to enforce carrying of data between partitions. Reputation is used as an analogue for the likelihood of nodes interacting with nodes from other partitions in the future. The number of copies of data shared with other nodes is inversely related to the nodes’ reputation. We use a real-world trace of Twitter to show how our implementation can converge to an equal number of copies as structured approaches@en

Devices running on Wireless Sensor Networks (WSNs) generally have limited energy resources, which makes it important to design energy-aware algorithms. Capacitated Minimum Spanning Tree (CMST) algorithms can be designed for finding energy-aware routing paths and for load-balancing among sub-trees connected to the sink device. Despite being studied extensively in central settings, there has not been any energy-efficient algorithm for the WSNs. The bit complexity of applying a central approach in the sink node is O(n2 logn) bits on a network having n nodes. In this work, we present the design of an algorithm which aims to solve CMST problem in WSNs and is based on Esau-Williams (E-W) algorithm. The bit complexity of the proposed algorithm is O(nlogn) bits. We compare the performance of the algorithm with the straightforward implementation of E-W where the problem is solved by the sink node and the result is sent to the other nodes. According to the computational results, our algorithm is more efficient than this version with respect to the energy consumption. Our algorithm (MCO) consumes up to 3 times less energy than central algorithm.@en

Fair allocation of flows in multicommodity networks has been attracting a growing attention. In Max-Min Fair (MMF) flow allocation, not only the flow of the commodity with the smallest allocation is maximized but also, in turn, the second smallest, the third smallest, and so on. Since the MMF paradigm allows to approximate the TCP flow allocation when the routing paths are given and the flows are elastic, we address the network routing problem where, given a graph with arc capacities and a set of origin-destination pairs with unknown demands, we must route each commodity over a single path so as to maximize the throughput, subject to the constraint that the flows are allocated according to the MMF principle. After discussing two properties of the problem, we describe a column generation based heuristic and report some computational results.@en

Fair allocation of flows in multicommodity networks has been attracting a growing attention. In Max-Min Fair (MMF) flow allocation, not only the flow of the commodity with the smallest allocation is maximized but also, in turn, the second smallest, the third smallest, and so on. Since the MMF paradigm allows to approximate the TCP flow allocation when the routing paths are given and the flows are elastic, we address the network routing problem where, given a graph with arc capacities and a set of origin-destination pairs with unknown demands, we must route each commodity over a single path so as to maximize the throughput, subject to the constraint that the flows are allocated according to the MMF principle. After discussing two properties of the problem, we describe a column generation based heuristic and report some computational results.@en

We present the first self-stabilizing algorithm for finding a maximal b-matching in arbitrary networks and under distributed unfair (adversarial) schedulers. The previous self-stabilizing b-matching algorithm presented by Goddard et al. in 2003 assumes central scheduler. We give proof for the correctness of our new algorithm for both unfair and fair schedulers, as well as the synchronous scheduler. Our algorithm stabilizes in O(Bm) steps under unfair scheduler and in O(n) rounds under distributed fair and synchronous schedulers, where n, m and B are the number of processors, the number of edges and the maximum capacity in the graph, respectively. The time complexity of distributed fair version of our algorithm is better than that of the transformation of Goddard et al.'s sequential self-stabilizing algorithm to the distributed fair one with the conflict manager of Gradinariu and Tixeuil (2007).@en

We present the first self-stabilizing algorithm for finding a maximal b-matching in arbitrary networks and under distributed unfair (adversarial) schedulers. The previous self-stabilizing b-matching algorithm presented by Goddard et al. in 2003 assumes central scheduler. We give proof for the correctness of our new algorithm for both unfair and fair schedulers, as well as the synchronous scheduler. Our algorithm stabilizes in O(Bm) steps under unfair scheduler and in O(n) rounds under distributed fair and synchronous schedulers, where n, m and B are the number of processors, the number of edges and the maximum capacity in the graph, respectively. The time complexity of distributed fair version of our algorithm is better than that of the transformation of Goddard et al.'s sequential self-stabilizing algorithm to the distributed fair one with the conflict manager of Gradinariu and Tixeuil (2007).@en

Weighted graph matching is one of the most fundamental graph theoretical problems used in network design, especially in wireless network services such as radio resource allocation, physical layer security, energy-efficient partner selection and optimizing storage capacity. In this paper we present a distributed heuristic which provides nearly-optimal weighted matchings in polynomial time. We also propose an algorithm to decrease the number of transmitted messages to provide energy-efficient operation. Our approaches assume the asynchronous communication model and small messages having O(log (n)) bits. These assumptions directly fit the battery powered wireless networks such as wireless ad hoc and sensor networks. To the best of our knowledge, we propose the first distributed weighted matching algorithm which benefits from augmentation of augmenting paths having size larger than 3 for these networks. We also provide results of our simulations on synthetic geometric graphs to model wireless networks. Extensive simulations reveal that our algorithm improves the approximation performances of the other weighted matching algorithms and closes the gap between the approximation ratio and the optimum up to 32%.@en

Graph matching is a fundamental graph theory problem which has a broad application range including information retrieval, pattern recognition, graph partitioning, chemical structure analysis, protein function prediction, backup placement and cellular coverage. This problem has gained attention in distributed computing as there are distributed matching algorithms with asymptotically guaranteed time bounds and approximation ratios. On the other side, we do not know the practical performance of these algorithms. In this paper, we provide a detailed performance evaluation of asynchronous distributed maximum weighted matching (MWM) algorithms. We assume a message-passing system in CONGEST model in which the message size is limited to O(log n) where n is the number of nodes. This model is popular for energy-efficient networks such as wireless sensor networks. We used a discrete event simulator, SimPy, to model the assumed network structures. We provide the implementations of Watthenhofer and Wattenhofer's algorithm, Hoepman's algorithm, Lotker et al.'s algorithm and Lotker et al.'s improvement algorithm. The results show that the greedy algorithm of Hoepman performed best in approximating the optimum result in all types of networks, even achieving an approximation ratio of 0.99 in some instances. To the best of our knowledge this is the first study which provides an extensive performance evaluation of distributed MWM algorithms.@en

Matching problem has been attracting a growing attention in network design, especially in wireless communication networks. Although there is an exact polynomial-time sequential algorithm for the weighted version of the problem, all the related distributed algorithms are approximation algorithms. In this paper we present a distributed heuristic which improves the weight of a given matching in time proportional to the number of nodes. Our algorithm assumes the asynchronous communication model in which the message size is limited to O (log n) bits. To the best of our knowledge, it is the first distributed weighted matching algorithm which benefits from augmentation of alternating paths having size larger than 3 and uses small messages. We also provide results of our simulations on random geometric graphs. Computational results show that our algorithm improves the approximated solutions of other weighted matching algorithms roughly by 1-3% and closes the gap between the approximation ratio and the optimum solution by 9-26%.@en

Self stabilization is an important paradigm for the autonomous recovery of a distributed system from transient failures such as energy depletion of nodes and disrupted connections. It has been used in wireless sensor networks (WSN) as these networks are expected to automatically recover from a transient fault without human intervention. Graph matching is fundamental a graph theory problem which has a broad application range in WSNs and it has been studied extensively in self-stabilizing settings. In this work, we build a simulation model and perform tests to evaluate the fault tolerance properties of self-stabilizing matching algorithms. To the best of our knowledge, this is the first practical evaluation of these algorithms. Considering WSNs, we assume distributed fair and synchronous schedulers. Simulation results have shown that there is a tradeoff between stabilization time of algorithms and the quality of their results. The improvement algorithms which has better lower bounds give better matchings at the cost of longer durations of instability.@en