A Distance-Based Data-Mule Scheduling Technique for Lesser Nodal Delay in Wireless Sensor Network

Nodal delay in wireless sensor network is an indisputable factor in the medium of communication. Factor such as changeability of communication devices, network topologies, packet-sizes, and transmission rate demands to develop data-mule queue scheduling technique. Our proposed data-mule scheduling technique accomplish this through simulations using standard software written in C# by controlling data-mule schedules that collects data from all the nodes connected to the hop. The scheme identifies the hierarchical positions of static source nodes and the distance of mobile source nodes from the hop with rescheduling based on the newly acquired distances. Source nodes applied with data-mule scheduling technique resulted to lower nodal delay. Transmission of packet-data is efficiently and effectively improved

Challenges for orchestration and instance selection of composite services in distributed edge clouds

Today's centralized cloud-computing infrastructures have not been designed with geo-localized, personalized, bandwidth/processing-intensive, real-time applications in mind. High network delay and low throughput can have a significant impact on the user experience. Instead, such services could be deployed in distributed service nodes at the edge of the network, closer to the user. In this paper we focus on composite services of which the components are running in different service nodes. We present a two-layer framework that provides service orchestration and instance selection. We present the orchestration mechanisms to enable the flexible re-use of components across different composite services. For the resolution layer of our framework, we present two modes of operation that combine network and service availability information for efficient per-request instance selection among a multitude of service replicas