Mutual exclusion (ME) is a fundamental problem for resource allocation in distributed systems, It is concerned with how the various processes access shared resources in a mutually exclusive way. Besides the classic ME problem, several variant problems have been proposed and studied. In this paper, drawing inspiration from the scenario of controlling autonomous vehicles at intersections, we have defined a new ME problem, called Local Group Mutual Exclusion (LGME), w here mutual exclusion is necessary only among the processes requesting overlap but not the same set of resources. In comparison with other variant problems of ME, LGME is more general but also more challenging. To solve the LGME problem, we propose a novel notion called strong coterie, which can handle the complex process relationship in LGME. Based on strong coterie, we have designed an ME algorithm, which can handle concurrent CS execution and message asynchrony. The correctness of our algorithm is rigorously proved.

A Generalized Mutual Exclusion Problem and Its Algorithm

A distributed k-mutual exclusion algorithm based on autonomic spanning trees

This paper discusses the generalized local version of critical section problems including mutual exclusion, mutual inclusion, k-mutual exclusion and l-mutual inclusion. When a pair of numbers (li, ki) is given for each process Pi, it is the problem of controlling the system in such a way that the number of processes that can execute their critical sections at a time is at least li and at most ki among its neighboring processes and Pi itself. We propose the first solution for the generalized local (li, |Ni| + 1)-critical section problem (i.e., the generalized local li-mutual inclusion problem). Additionally, we show the relationship between the generalized local (li, ki)-critical section problem and the generalized local (|Ni| + 1 − ki, |Ni| + 1 − li)-critical section problem. Finally, we propose the first solution for the generalized local (li, ki)-critical section problem for arbitrary (li, ki), where 0 ≤ li < ki + |Ni| + 1 for each process Pi.

/pdf/an-asynchronous-message-passing-distributed-algorithm-for-2zo8u3ocr4.pdf

An Asynchronous Message-Passing Distributed Algorithm for the Generalized Local Critical Section Problem

We present in this paper a fault tolerant permission-based k-mutual exclusion algorithm, which is an extension of Raymond's algorithm. Tolerating up to n-1 failures, our algorithm keeps its effectiveness despite failures. It uses information provided by unreliable failure detectors to dynamically detect crashes of nodes. Performance evaluation experiments show the performance of our algorithm compared to Raymond's when faults are injected.

Fault Tolerant K-Mutual Exclusion Algorithm Using Failure Detector

Generalized distributed mutual exclusion algorithms allow processes to concurrently access a set of shared resources. However, they must ensure an exclusive access to each resource. In order to avoid deadlocks, many of them are based on the strong assumption of a prior knowledge about conflicts between processes' requests. Some other approaches, which do not require such a knowledge, exploit broadcast mechanisms or a global lock, degrading message complexity and synchronization cost. We propose in this paper a new solution for shared resources allocation which reduces the communication between non-conflicting processes without a prior knowledge of processes conflicts. Performance evaluation results show that our solution improves resource use rate by a factor up to 20 compared to a global lock based algorithm.

/pdf/reducing-synchronization-cost-in-distributed-multi-resource-q5rch3zzhw.pdf

Reducing Synchronization Cost in Distributed Multi-resource Allocation Problem

k-mutual exclusion is an important problem for resource-intensive peer-to-peer applications ranging from aggregation to file downloads. In order to be practically useful, k-mutual exclusion algorithms not only need to be safe and live, but they also need to be fair across hosts. We propose a new solution to the k-mutual exclusion problem that provides a notion of time-based fairness. Specifically, our algorithm attempts to minimize the spread of access time for the critical resource. While a client's access time is the time between it requesting and accessing the resource, the spread is defined as a system-wide metric that measures some notion of the variance of access times across a homogeneous host population, e.g., difference between max and mean. We analytically prove the correctness of our algorithm, and evaluate its fairness experimentally using simulations. Our evaluation under two settings - a LAN setting and a WAN based on the King latency data set - shows even with 100 hosts accessing one resource, the spread of access time is within 15 seconds.

/pdf/fair-k-mutual-exclusion-algorithm-for-peer-to-peer-systems-2rgas6o03c.pdf

Fair K Mutual Exclusion Algorithm for Peer to Peer Systems

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Fair K Mutual Exclusion Algorithm for Peer to Peer Systems