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In the realm of artificial intelligence, Federated Learning(FL) has emerged as a promising technique. FL enables AI models to be trained collaboratively without compromising privacy by directly sharing sensitive data. Specifically, FL based on the Gossip protocol in peer-to-peer networks can enhance efficiency by leveraging the local data of each client and optimizing traffic distribution. However, the reliability of FL is not always guaranteed, leading to potential security risks such as data leakage. To address these challenges, this paper proposes a secure push-pull hybrid Gossip protocol based on two-pass mutual authentication. The protocol ensures mutual authentication, integrity, and confidentiality by generating and sharing NONCE values with the receiver in a single push and pull process. This fosters trust among clients in the peer-to-peer network environment, enabling them to generate accurate aggregated models Wagg based on decrypted model updates Ws. This research contributes to the development of advanced FL strategies that prioritize efficient communication, security, and accuracy in peer-to-peer network environments. [ABSTRACT FROM AUTHOR]

Aiming at the problems of mobile ad hoc networks, such as limited network coverage, unstable connection, and vulnerability to malicious attacks when nodes cooperate, this paper combined with blockchain technology to increase the security and integrity of data and proposed a blockchain model for mobile ad hoc networks based on Hashgraph. Firstly, this paper designed a clustering algorithm, which divides the nodes into different clusters, selects cluster heads to count the number of nodes in the cluster, and writes them to events for propagation to ensure the smooth progress of consensus; Secondly, it optimized the Gossip protocol, and proposed the FS-Gossip（Fast Spreading Gossip）protocol, which reduces the blindness of neighbor node selection, improves the propagation efficiency, and increases the detection speed of new cluster nodes; Finally, it improved the complex consensus calculation in Hashgraph, and proposed a propagation mechanism based on cluster head priority. The lightweight consensus and propagation mechanism is applied to nodes in the cluster to speed up event confirmation, reduce delay, and improve throughput. The simulation results verify the advantages of the model in terms of delay, throughput and propagation efficiency. [ABSTRACT FROM AUTHOR]

A gossip protocol is a procedure for sharing secrets in a network. The basic action in a gossip protocol is a pairwise message exchange (telephone call) wherein the calling agents exchange all the secrets they know. An agent who knows all secrets is an expert. The usual termination condition is that all agents are experts. Instead, we explore protocols wherein the termination condition is that all agents know that all agents are experts. We call such agents super experts. We also investigate gossip protocols that are common knowledge among the agents. Additionally, we model that agents who are super experts do not make and do not answer calls, and that this is common knowledge. We investigate conditions under which protocols terminate, both in the synchronous case, where there is a global clock, and in the asynchronous case, where there is not. We show that a commonly known protocol with engaged agents may terminate faster than the same commonly known protocol without engaged agents. [ABSTRACT FROM AUTHOR]

The distributed composite optimization problem associated a multi-agent network is investigated in this paper. Different from conventional optimization issues, the cost function of composite optimization consists of a convex function and a regularization function (possibly nonsmooth). The gossip protocol is also introduced to enhance the robustness of the network, and a gossip-based distributed composite mirror descent algorithm is presented to deal with the previous problem, which adopts the asynchronous communication method. Moreover, the algorithm performance is analyzed and the theoretical results on the corresponding error bounds are obtained. Finally, the distributed logistic regression is provided as an example to validate the practicability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Federated Learning is a machine learning strategy that is communication-efficient and privacy-preserved. However, Federated Learning in a P2P network environment to provide high scalability requires a larger amount of communications than a server-client. Therefore, we propose FedSnM that Federated Learning strategy using Score-and-Model, which sends the Score derived from the Federated Learning training process in the preceding Push Gossip process and receives the Model trained from the data held by each client in the Pull Gossip process. FedSnM reduces the total number of communications by 88.5% and improves the accuracy by 4.26% compared with FedAvg. In addition, FedSnM improves the bottleneck by reducing the communication cost by 68.3% based on the client who performed the most communication compared with FedPSO. In the future, FedSnM can evolve into the learning strategy in an asynchronous network that has different communication speeds through improved Gossip Protocol. [ABSTRACT FROM AUTHOR]

The increase of the Internet of Things (IoT) calls for secure solutions for industrial applications. The security of IoT can be potentially improved by blockchain. However, blockchain technology suffers scalability issues which hinders integration with IoT. Solutions to blockchain's scalability issues, such as minimizing the computational complexity of consensus algorithms or blockchain storage requirements, have received attention. However, to realize the full potential of blockchain in IoT, the inefficiencies of its inter-peer communication must also be addressed. For example, blockchain uses a flooding technique to share blocks, resulting in duplicates and inefficient bandwidth usage. Moreover, blockchain peers use a random neighbor selection (RNS) technique to decide on other peers with whom to exchange blockchain data. As a result, the peer-to-peer (P2P) topology formation limits the effective achievable throughput. This paper provides a survey on the state-of-the-art network structures and communication mechanisms used in blockchain and establishes the need for network-based optimization. Additionally, it discusses the blockchain architecture and its layers categorizes existing literature into the layers and provides a survey on the state-of-the-art optimization frameworks, analyzing their effectiveness and ability to scale. Finally, this paper presents recommendations for future work. [ABSTRACT FROM AUTHOR]

Blockchain is a distributed digital ledger consisting of sequence of blocks. These blocks are groups of transactions that make up a sequence where each block contains the cryptographic hash of its prior block. To maintain huge networks, data integrity, and consistency some blockchain deployments uses a distributed communication method known as gossip protocol. In gossip protocol, every node/system relays any recent data to all its neighbors in an atomic fashion where each neighbor imitates the process until the whole system is synchronized. The number of iterations required to synchronize N hosts is O (log N) despite the failing nodes and data losses in transmission. However, the protocol is not cost effective when it comes to number of state exchanges and the transmission delay due to the redundant state information exchanges. To make gossip protocol more efficient; first, we propose a fail-proof algorithm that can be used under zero node failure scenarios; secondly, an opportunistic algorithm giving a rational, stable, and predictable correction phase and lastly a checking algorithm that obtains an iterative correction until a convergence or a synchronization across all the nodes in the system are reached. We implement these improvements and carefully analyze and demonstrate our findings. [ABSTRACT FROM AUTHOR]

As a result of the proliferation of digital and network technologies in all facets of modern society, including the healthcare systems, the widespread adoption of Electronic Healthcare Records (EHRs) has become the norm. At the same time, Blockchain has been widely accepted as a potent solution for addressing security issues in any untrusted, distributed, decentralized application and has thus seen a slew of works on Blockchain-enabled EHRs. However, most such prototypes ignore the performance aspects of proposed designs. In this paper, a prototype for a Blockchain-based EHR has been presented that employs smart contracts with Hyperledger Fabric 2.0, which also provides a unified performance analysis with Hyperledger Caliper 0.4.2. The additional contribution of this paper lies in the use of a multi-hosted testbed for the performance analysis in addition to far more realistic Gossip-based traffic scenario analysis with Tcpdump tools. Moreover, the prototype is tested for performance with superior transaction ordering schemes such as Kafka and RAFT, unlike other literature that mostly uses SOLO for the purpose, which accounts for superior fault tolerance. All of these additional unique features make the performance evaluation presented herein much more realistic and hence adds hugely to the credibility of the results obtained. The proposed framework within the multi-host instances continues to behave more successfully with high throughput, low latency, and low utilization of resources for opening, querying, and transferring transactions into a healthcare Blockchain network. The results obtained in various rounds of evaluation demonstrate the superiority of the proposed framework. [ABSTRACT FROM AUTHOR]

Single copy Distributed Software Transactional Memory protocol maintains only one replica of each object in the system and is therefore prone to failures in large scale dynamically changing network. In this paper we propose a replication model using quorum system for transactional memory protocol where communication among the nodes takes place using gossip. The previous protocols demand a static structure over the network. Maintenance of a static structure for a dynamic network requires a significant overhead. Our method executes on an unstructured network which does not require adaption in case of node joining and node leaving. The algorithm maintains the coherence of the objects and aims to achieve low communication cost while reducing execution time of the transactions. The algorithm achieves a message complexity of O n and time complexity of O log n which is an improvement over previous replication protocols for distributed transactional memory. Simulation results shows that the method exhibits better fault tolerance and requires less number of messages than existing approaches. [ABSTRACT FROM AUTHOR]

This study develops a gossip‐based distributed hierarchical algorithm to solve the constrained convex optimisation problem over a multi‐cluster network. Different from the existing works with incremental communication approach, a gossip protocol is applied to achieve inter‐cluster information exchange. At each iteration, only two neighbour clusters are randomly woken up to exchange their new updates while others keep their latest information, which relaxes the restrictions on the inter‐cluster communication topology. Technically, to investigate the intra‐cluster consensus, a new analysing approach is exploited and some different techniques including the non‐expansiveness of projection operator and the supermartingale convergence results are employed, based on which it is proved that estimates of all agents in the multi‐cluster network jointly converge to the optimal solution with probability one. A numerical example on constrained lasso regression is provided to validate the theoretical results. [ABSTRACT FROM AUTHOR]

A gossip protocol is a procedure for spreading secrets among a group of agents, using a connection graph. The goal is for all agents to get to know all secrets, in which case we call the execution of the protocol successful. We consider distributed and dynamic gossip protocols. In distributed gossip, the agents themselves instead of a global scheduler determine whom to call. In dynamic gossip, not only secrets are exchanged but also telephone numbers (agent identities). This results in increased graph connectivity. We define six such distributed dynamic gossip protocols, and we characterize them in terms of the topology of the graphs on which they are successful, wherein we distinguish strong success (the protocol always terminates, possibly assuming fair scheduling) from weak success (the protocol sometimes terminates). For five of these protocols, strong success (fair) and weak success are characterized by weakly connected graphs. This result is surprising, because the protocols are fairly different. In the sixth protocol, an agent may only call another agent if it does not know the other agent's secret. Strong success for this protocol is characterized by graphs for which the set of non-terminal nodes is strongly connected. Weak success for this protocol is characterized by weakly connected graphs satisfying further topological constraints that we define in the paper. One direction of this characterization is surprisingly harder to prove than the other results in this contribution. [ABSTRACT FROM AUTHOR]

A distributed system guarantees the acceptance of Byzantine fault tolerance (BFT) for information transmission. Practical BFT (pBFT) and asynchronous BFT (aBFT) are among the various available forms of BFT. Distributed systems generally share information with all participating nodes. After information is shared, the systems reshare it. Thus, ensuring BFT consumes a considerable amount of time. Herein, we propose Decision search protocols that apply the gossip protocol, denoted by DecisionBFT, for distributed networks with guaranteed BFT. Each protocol in DecisionBFT is completely asynchronous and leaderless; it has an eventual consensus but no round-robin or proof-of-work. The core concept of the proposed technology is the consensus structure, which is based on the directed acyclic graph (DAG) and gossip protocol. In the most general form, each node in the algorithm has a set of k neighbors of most preference. When receiving transactions, a node creates and connects an event block with all its neighbors. Each event block is signed by the hashes of the creating node and its k peers. The consensus structure of the event blocks utilizes a DAG, which guarantees aBFT. The proposed framework uses Lamport timestamps and concurrent common knowledge. Further, an example of a Decision search algorithm, based on the gossip protocol DecisionBFT, is presented. The proposed DecisionBFT protocol can reach a consensus when 2/3 of all participants agree to an event block without any additional communication overhead. The DecisionBFT protocol relies on a cost function to identify the k peers and generate the DAG-based consensus structure. By creating a dynamic flag table that stores connection information between blocks, the gossip protocol achieves a consensus in fewer steps than that in the case of the existing aBFT protocol.

Decentralized clustering of modern information technology is widely adopted in various fields these years. One of the main reason is the features of high availability and the failure-tolerance which can prevent the entire system form broking down by a failure of a single point. Recently, toolkits such as Akka are used by the public commonly to easily build such kind of cluster. However, clusters of such kind that use Gossip as their membership managing protocol and use link failure detecting mechanism to detect link failures cannot deal with the scenario that a node stochastically drops packets and corrupts the member status of the cluster. In this paper, we formulate the problem to be evaluating the link quality and finding a max clique (NP-Complete) in the connectivity graph. We then proposed an algorithm that consists of two models driven by data from application layer to respectively solving these two problems. Through simulations with statistical data and a real-world product, we demonstrate that our algorithm has a good performance. [ABSTRACT FROM AUTHOR]

We provide a logical investigation of a simple case of communication in a network of agents called the gossip problem. Its classical version is: given n agents each of which has a secret -- a fact not known to anybody else --, how many calls does it take to achieve shared knowledge of all secrets, i.e., to reach a state where every agent knows every secret? Several protocols achieving shared knowledge in 2(n -- 2) calls exist and were proved to be optimal: no shorter sequence of calls exists. We generalize that problem and focus on higher-order shared knowledge: how many calls does it take to obtain that everybody knows that everybody knows all secrets? More generally, how many calls does it take to obtain shared knowledge of order k? This cannot be achieved simply by communicating facts: the agents also have to communicate higher-order knowledge of facts. We give an algorithm that works in (k + 1)(n -- 2) calls. We analyse its properties in a logic that we have investigated in previous work and that is based on the concept of observability of propositional variables by agents: Dynamic Epistemic Logic of Propositional Assignment and Observation DEL-PAO. This enables us in particular to give a formal proof of correctness of the algorithm. [ABSTRACT FROM AUTHOR]

SUMMARY To detect deadlock in distributed systems, the initiator should construct an efficient explicit or implicit global wait-for graph. In this paper, we present an unstructured deadlock detection algorithm using a gossip protocol in cloud computing environments, where constituting nodes may join and leave at any time. Because of the inherit properties of a gossip protocol, we argue that our proposed deadlock detection algorithm is scalable, fault-tolerant, and efficient, retaining safety and liveness properties. The correctness proof of the algorithm is also provided. The message complexity of our proposed algorithm is O( n), where n is the number of nodes. Our performance evaluation with scalable settings shows that our approach has a significant advantage over previous deadlock detection algorithms in terms of solving scalability, fault-tolerance, and complexity-efficiency issues. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Cloud computing offers computational, storage, and applications capabilities as subscription oriented services. It offers a platform explore computational assets and use them based on "pay per use arrangement". Thus it opens ways to access boundless assets with negligible equipment and programming at the customers' end. This paper focuses on the advancement of a cloud administration's provisioning structure by building up a dynamic load-balancer for the cloud. It proposes a framework and protocol for the resource environment in the cloud. Distributed Hash Table (DHT) protocol has been utilized for a service query to perform a job agreed by the user. For load balancing, gossip protocol has been used for inter/intra-cluster gossip. For inter-cluster gossip, the load is balanced among the leaders of every cluster. The proposed protocol uses the inter-cloud resource management, where a leader is selected from the cloud that interacts to other cloud and decides on virtual machine (VM) migration. The decision about job allocation is not acknowledged by a single machine, which generates the scalable architecture of the proposed protocol. The protocol considers the current load situation and decides at the time of request submission. This protocol is adaptable, reliable and scalable and supports green computing by utilizing server solidification. [ABSTRACT FROM AUTHOR]

A distributed system guarantees the acceptance of Byzantine fault tolerance (BFT) for information transmission. Practical BFT (pBFT) and asynchronous BFT (aBFT) are among the various available forms of BFT. Distributed systems generally share information with all participating nodes. After information is shared, the systems reshare it. Thus, ensuring BFT consumes a considerable amount of time. Herein, we propose Decision search protocols that apply the gossip protocol, denoted by DecisionBFT, for distributed networks with guaranteed BFT. Each protocol in DecisionBFT is completely asynchronous and leaderless; it has an eventual consensus but no round-robin or proof-of-work. The core concept of the proposed technology is the consensus structure, which is based on the directed acyclic graph (DAG) and gossip protocol. In the most general form, each node in the algorithm has a set of k neighbors of most preference. When receiving transactions, a node creates and connects an event block with all its neighbors. Each event block is signed by the hashes of the creating node and its k peers. The consensus structure of the event blocks utilizes a DAG, which guarantees aBFT. The proposed framework uses Lamport timestamps and concurrent common knowledge. Further, an example of a Decision search algorithm, based on the gossip protocol DecisionBFT, is presented. The proposed DecisionBFT protocol can reach a consensus when 2/3 of all participants agree to an event block without any additional communication overhead. The DecisionBFT protocol relies on a cost function to identify the k peers and generate the DAG-based consensus structure. By creating a dynamic flag table that stores connection information between blocks, the gossip protocol achieves a consensus in fewer steps than that in the case of the existing aBFT protocol. [ABSTRACT FROM AUTHOR]

In large-scale distributed-computing environments, numerous factors may affect the predictable performance of load balancing policies causing variable load distribution in the network and bottlenecks. This paper presents a two-level load balancing algorithm for solving the dynamic load balancing problem considering the loss of processors and connectivity of the network. The proposed method privileges local load balancing over global load balancing thus reduces the communication cost over the global network. To further minimize communication costs and to handle loss of connectivity, the algorithm proposes a new communication model for global communication among the processors. The performance, correctness, and scalability of the algorithm are analyzed which show that our algorithm requires O(log m) rounds and O(m log m) messages for m clusters and achieves minimum cluster and global load deviation. Simulation results also support our analytical studies. [ABSTRACT FROM AUTHOR]