An Advanced Algorithm for Higher Network Navigation in Social Internet of Things Using Small-World Networks.

摘要: The Internet of Things (IoT) is a recent evolutionary technology that has been the primary focus researchers for last two decades. In IoT, an enormous number objects are connected together using diverse communications protocols. As result this massive object connectivity, search exact service from difficult, and hence issue scalability arises. order to resolve issue, idea integrating social networking concept into generally referred as Social (SIoT) was introduced. SIoT gaining popularity attracting attention research community due its flexible spacious nature. SIoT, have ability find desired in distributed manner by their neighbors. Although technique proven be efficient, heterogeneous devices growing so exponentially problems can exist right or huge devices. better analyze performance services domain, there need impose certain set rules on these objects. Our novel contribution study address link selection problem proposing algorithm follows key properties navigability small-world networks, such clustering coefficients, path lengths, giant components. empowers restricting connections objects, eliminating old links having fewer connections. We performed extensive series experiments real network data sets sites like Brightkite Facebook. expected results demonstrate our especially terms reducing length increasing average coefficient. Finally, it reflects overall achieving easier navigation. easily applied single node even entire network.