Abstract
Home networks continue to experience an increase in the number of devices and services. This increase has come as a result of rapid technological revolutions in engineering and telecommunication industries. The advancement in technology has enabled access of intelligent home networks locally as well as remotely. This in turn has led to poor quality of service (QoS) to the consumers of such services and applications. Therefore, in this chapter, we present performance optimization of intelligent home network model that is scalable and adaptable to these increases and technological changes. We segmented and prioritized the intelligent home network into six subnets. Then we assigned weighing factor numbers to the devices, which aided in their classification and prioritization. We then grouped the supported home network services and applications into six classes and increased the number of transmitted packets per iteration in each Class of Service (CoS). We tested and evaluated proposed model using OMNET++ simulator against Priority Queuing (PQ) and Class-Based Weighted Fair Queuing (CBWFQ) models. The results show an average network packet throughput of 99.74 %, delay of 3.02 s, and loss of 1.59 %.
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Kevin, K.M., Kogeda, O.P., Lall, M. (2016). Performance Optimization of Intelligent Home Networks. In: Mahmood, Z. (eds) Connectivity Frameworks for Smart Devices. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-33124-9_9
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DOI: https://doi.org/10.1007/978-3-319-33124-9_9
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