Fog computing allows computationally-heavy problems with tight time constraints to be solved even if end devices have limited computational resources and latency induced by cloud is too high. How can energy consumed fog saved while obeying considering not only computations but also transmission through wireless wired links? This work examines the consumption sources in networks discusses models...

Abstract Under many scenarios where resources may be scarce or a good Quality of Service is requirement, appropriately sizing components and devices one the main challenges. New scenarios, such as IoT, mobile cloud computing, edge computing fog have emerged recently. The ability to design, model simulate those infrastructures critical dimension them correctly. Queuing theory models provide appr...

Fog computing enables the execution of IoT applications on compute nodes which reside both in cloud and at edge network. To achieve this, most fog systems route data a path starts source, goes through various nodes. Each node this may accept if there are available resources to process locally. Otherwise, is forwarded next path. Notably, when (rather than accepted), communication latency increas...

Fog computing provides an effective solution to various problems by extending the cloud’s functionality typically more limited units closer user devices. can provide a higher level of experience due its geographic and network topology location distribution. IoT services also need be managed seamlessly ensure adequate QoS (due mobility devices or temporary periods without internet connection). S...

Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity constraints. One introduced methods solve these fog which makes closer devices. A system for congestion managemen...