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Mobile entities with wireless links are able to form a mobile ad-hoc network. Such an infrastructureless network does not have to be administrated. However, self-organizing principles have to be applied to deal with upcoming problems, e.g. information dissemination. These kinds of problems are not easy to tackle, requiring complex algorithms. Moreover, the usefulness of pure ad-hoc networks is arguably limited. Hence, enthusiasm for mobile ad-hoc networks, which could eliminate the need for any fixed infrastructure, has been damped. The goal is to overcome the limitations of pure ad-hoc networks by augmenting them with instant Internet access, e.g. via integration of UMTS respectively GSM links. However, this raises multiple questions at the technical as well as the organizational level. Motivated by characteristics of small-world networks that describe an efficient network even without central or organized design, this paper proposes to combine mobile ad-hoc networks and infrastructured networks to form hybrid wireless networks. One main objective is to investigate how this approach can reduce the costs of a permanent backbone link and providing in the same way the benefits of useful information from Internet connectivity or service providers. For the purpose of bridging between the different types of networks, an adequate middleware service is the focus of our investigation. This paper shows our first steps forward to this middleware by introducing the Injection Communication paradigm as principal concept.
Cross-stakeholder service orchestration is a generalization of 5G network slices which has potential to increase business agility in Beyond 5G (B5G). An architectural framework is proposed which enables domain operators to expose their functionalitie
We consider a multihop wireless system. There are multiple source-destination pairs. The data from a source may have to pass through multiple nodes. We obtain a channel scheduling policy which can guarantee end-to-end mean delay for the different tra
Control of wireless multihop networks, while simultaneously meeting end-to-end mean delay requirements of different flows is a challenging problem. Additionally, distributed computation of control parameters adds to the complexity. Using the notion o
Control of multihop Wireless networks in a distributed manner while providing end-to-end delay requirements for different flows, is a challenging problem. Using the notions of Draining Time and Discrete Review from the theory of fluid limits of queue
Wireless traffic attributable to machine learning (ML) inference workloads is increasing with the proliferation of applications and smart wireless devices leveraging ML inference. Owing to limited compute capabilities at these edge devices, achieving