DESIGN AND IMPLEMENTATION  OF A GROUP MUTUAL EXCLUSION IN OPPORTUNISTIC NETWORK

DESIGN AND IMPLEMENTATION  OF A GROUP MUTUAL EXCLUSION IN OPPORTUNISTIC NETWORK

Abstract:
Opportunistic networks are a type of decentralized network where communication occurs intermittently, and nodes exploit sporadic encounters to exchange information. These networks are characterized by their dynamic and unpredictable nature, making traditional approaches to mutual exclusion impractical. Group mutual exclusion is a crucial aspect of resource management in opportunistic networks, ensuring that shared resources are accessed in a mutually exclusive manner by multiple nodes simultaneously.

This paper presents a comprehensive review of group mutual exclusion in opportunistic networks, focusing on the challenges, existing solutions, and future research directions. The challenges in achieving group mutual exclusion in opportunistic networks arise due to the absence of a central authority, node mobility, and intermittent connectivity. Moreover, the resource constraints and heterogeneity of nodes further complicate the problem.

Existing solutions for group mutual exclusion in opportunistic networks can be broadly categorized into three classes: centralized, distributed, and hybrid approaches. Centralized approaches rely on a central authority to manage resource access, but they suffer from single point failures and scalability issues. Distributed approaches employ decentralized protocols to achieve mutual exclusion, leveraging message passing and coordination among nodes. Hybrid approaches combine both centralized and distributed mechanisms to exploit the advantages of both paradigms.

This review highlights the strengths and limitations of existing approaches and discusses their applicability in different scenarios. It also identifies several open research challenges, such as scalability, adaptability to dynamic network conditions, fault tolerance, and energy efficiency. Furthermore, emerging technologies, such as blockchain and machine learning, offer promising avenues for addressing these challenges.

In conclusion, group mutual exclusion in opportunistic networks is a complex problem that requires innovative solutions tailored to the unique characteristics of these networks. This review provides a comprehensive overview of the state-of-the-art in this field, serving as a valuable resource for researchers and practitioners working on resource management in opportunistic networks. By addressing the identified challenges and exploring new directions, we can advance the development of efficient and reliable group mutual exclusion mechanisms in opportunistic networks

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