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Distributed systems

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Distributed systems

 

Introduction

Distributed systems involve the interaction of many devices operating individually but sharing the same memory storage on a network. Having extensive interconnections leads to complex management of objects and processes. To achieve numerous health operations and reliability of these devices, mechanisms to detect faults were developed. However, eruptions of problems have reduced the effectiveness of fault detection in distributed systems.

Problems

Fault detectors are mainly built to prevent mistakes that may occur in the system and alters the functionality and normal running of the system. Although they prevent the system from such occurrence, fault still persists due to the model nature of the distributed system. Distributed system failures are regarded as non-deterministic. They are partial faults that occur unpredictably. They usually happen at any time in the system, making it hard for the system detectors to recognize such failures (Lamport, Shoutak, 2019).

According to Lamport (2019), system failure allows some application programs to run despite system errors, while others are entirely corrupted and crashed.  The behavior arises due to many interconnections and becomes difficult to identify faulty programs and non-faulty. Thus, it becomes a hazard in system failure detection and maintenance.

The main aim of system fault detectors is to enhance system tolerance. In some instances, it becomes problematic due to unreliable failure detectors mixed with reliable failure detectors. They become unreliable when they cannot heighten system resistance to breakdowns. Some failures come and disappear. Some replicate and manifest under unknown conditions. In complex systems, it is difficult to observe and detect such manifestations while other faults occur independently.

Mostly, a fault occurs in all stages of logical operations. During the communication levels, information is distributed asynchronously on a network. If the system is unreliable enough, requests end up being paused, some queued, and some files end up lost in the network. It is difficult to trace errors or faults over the asynchronous transmission. In other cases, error information is not displayed at all. The network is a powerful resource in the distributed system; its functionalities are cut off whenever there is a fault (Lakshman & Malik, 2010).

Asynchronous communication also deals with sessions waiting time for requests and services. When request time is short, nodes are engaged and assigned to another service. If the request dies before submission, responsibilities are transferred to another node for the same service. This long waiting time becomes problematic to the system. For instance, if a system is shut down in the process or removed from the network, all the nodes end the session and die. This ends up causing successive system failures, which then affects the system’s shared memory before spreading to the whole system.

Conclusion

System fault detectors do not promise complete competence and correctness of the system. They sometimes fail to meet the intended purpose due to some unknown and unreliable cases. Thus, it is vital to building systems that show known operations that can be relied upon towards fault elimination in distributed systems.

 

 

Works Cited

Lamport, L., Shostak, R., & Pease, M. (2019). The Byzantine generals problem. In Concurrency: the Works of Leslie Lamport (pp. 203-226).

Lakshman, A., & Malik, P. (2010). Cassandra: a decentralized structured storage system. ACM SIGOPS Operating Systems Review44(2), 35-40.

Lamport, L. (2019). Time, clocks, and the ordering of events in a distributed system. In Concurrency: the Works of Leslie Lamport (pp. 179-196).

 

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