Performance modeling of the middleware overlay infrastructure of mobile things

Abstract

Internet of Things (IoT) applications consist of diverse Things (sensors and devices) in terms of hardware resources. Furthermore, such applications are characterized by the Things' mobility and multiple interaction types, such as synchronous, asynchronous, and streaming. Middleware IoT protocols consider the above limitations and support the development of effective applications by providing several Quality of Service features. These features aim to enable application developers to tune an application by switching different levels of response times and delivery success rates. However, the profusion of the developed IoT protocols and the intermittent connectivity of mobile Things, result to a non-trivial application tuning. In this paper, we model the performance of the middleware overlay infrastructure using Queueing Network Models. To represent the mobile Thing's connections/disconnections, we model and solve analytically an ON/OFF queueing center. We apply our approach to Streaming interactions with mobile peers. Finally, we validate our model using simulations. The deviations between the performance results foreseen by the analytical model and the ones provided by the simulator are shown to be less than 5%.

Characterizing Delay and Control Traffic of the Cellular MME With IoT Support

“…Analytical models of IoT systems have been developed for specific application use cases, like management [26], opportunistic crowd sensing in vehicular scenarios [27], or ambient backscatter devices [28]. Other works have presented theoretical models for the study of networking aspects such as the performance of middleware protocols [29], implemented between the application and the transport layer, or of the random access procedure in NB-IoT [30], [31]. Note, however, that none of the above works investigates the critical role of the EPC control plane in IoT-based systems; indeed few studies exist on the characterization of the overhead and service delay when the EPC handles massive IoT data traffic.…”

Automated synthesis of mediators for middleware-layer protocol interoperability in the IoT

“…With respect to concurrency semantics, a dedicated virtual channel is used between a sender and a receiver. Items sent by different servers will be received (or not) by the designated clients, based on the offered QoS guarantees of the underlying infrastructure [35]. Regarding synchronization semantics, CS supports one-way, two-way asynchronous and two-way synchronous interactions.…”

“…With respect to concurrency semantics, the broker maintains a dedicated buffer for each subscriber. Hence, unless an event expires, or the PS QoS guarantees [35] do not support event persistence, all events sent by different publishers will be eventually received by interested subscribers. Furthermore, existing PS middleware protocols support several synchronization semantics between subscribers and the broker.…”

“…In terms of concurrency semantics, multiple consumers can receive streams of data from multiple producers over dedicated virtual channels. Hence, depending on the QoS guarantees [35] of the underlying communication infrastructure, all streamed data can be received successfully (or not) by the designated consumers. Regarding synchronization semantics, consumers receive asynchronously each arriving piece of data.…”

QoS-Aware Resource Allocation for Mobile IoT Pub/Sub Systems

“…To support the development of effective applications under the constraints found in the IoT (i.e., intermittent connectivity, obsolete data feeds, etc), pub/sub protocols provide several Quality of Service (QoS) features [10]. These features aim to enable application developers to tune an application by configuring its QoS metrics at different levels such as end-to-end response times and delivery success rates.…”