IoT Short-range Network protocols: Analytical study and operating models

Analytical Loss Models for MAC Protocols in Optical Ring Network Operating under a Static Traffic Load

In this paper we analyse previously proposed MAC protocols for optical ring networks under static traffic conditions. The analytical models are developed for random order and round-robin transmission policies in both slotted and unslotted cases. The models predict the receiver efficiency, i.e. the fraction of time each receiver is active. The models are also verified by numerical simulations an...

Implementing Bounded Linear Programming and Analytical Network Process Fuzzy Models to Motivate Employees: a Case Study

In this research, the factors affectinguniversity employees’ motivation and productivity are identified and classified in seven groups; the impact of each motivation factor on the productivity is presented by ANP fuzzy model.Eight universities in Iran were analyzed in this research work. The aim of this study is to explore the productivity of employees. This paper attempts to give new insights ...

Network-aware Publish-Subscribe Protocols for IoT scenarios

Application protocols employing the publish-subscribe messaging pattern provide many advantages for IoT scenarios. For instance, the Message Queue Telemetry Transport (MQTT) tolerates long breaks in connectivity and provides low energy consumption. However, there is lack of research on the behavior of such protocols under challenging scenarios. Preliminary studies show that mobility affect the ...

RESTful IoT Authentication Protocols

Multi-modal network protocols : adapting to highly variable operating conditions

Most network protocols are uni-modal: they employ a single set of algorithms that allows them to cope well only within a narrow range of operating conditions. This rigid design renders these protocols inefficient in the face of widely varying operating environments or in conditions different from the ones for which they are optimized. Such uni-modal protocols have great difficulty in the mobile...