High Performance Priority Packets Scheduling Mechanism for Big Data in Smart Cities

Today,Internet of Things(IoT)is a technology paradigm which convinces many researchers for the purpose of achieving high performance of packets delivery in IoT applications such as smart cities.Interconnecting various physical devices such as sensors or actuators with the Internet may causes different constraints on the network resources such as packets delivery ratio,energy efficiency,end-to-end delays etc.However,traditional scheduling methodologies in large-scale environments such as big data smart cities cannot meet the requirements for high performance network metrics.In big data smart cities applications which need fast packets transmission ratio such as sending priority packets to hospitals for an emergency case,an efficient schedulingmechanism ismandatory which is the main concern of this paper.In this paper,we overcome the shortcoming issues of the traditional scheduling algorithms that are utilized in big data smart cities emergency applications.Transmission information about the priority packets between the source nodes(i.e.,people with emergency cases)and the destination nodes(i.e.,hospitals)is performed before sending the packets in order to reserve transmission channels and prepare the sequence of transmission of theses priority packets between the two parties.In our proposed mechanism,Software Defined Networking(SDN)with centralized communication controller will be responsible for determining the scheduling and processing sequences for priority packets in big data smart cities environments.In this paper,we compare between our proposed Priority Packets Deadline First scheduling scheme(PPDF)with existing and traditional scheduling algorithms that can be used in urgent smart cities applications in order to illustrate the outstanding network performance parameters of our scheme such as the average waiting time,packets loss rates,priority packets end-to-end delay,and efficient energy consumption.

Call admission control scheme for real-time services in packet-switched OFDM wireless networks

A call admission control scheme is proposed for real-time services in packet-switched orthogonal frequency division multiplexing （OFDM） wireless cellular networks. The main idea of the proposed scheme is to use maximum acceptance ratio to maintain maximum channel utilization for real-time services according to the desired packet-level and call- level quality-of-service （QoS） requirements. The acceptance ratio is periodically adjusted by using a time discrete Markov chain and Wiener prediction theory according to the varying traffic load. Extensive simulation results show that this algorithm maintains high channel utilization, even as it guarantees packet-level and call-level QoS requirements for real-time services.

SIR approach in modeling data packets forwarding at a leaky bucket

When network users are intensively interacting during rush hour,avoiding data loss and latency is a concern in guaranteeing segment reliability.Implementing a leaky bucket could be needed to achieve flows effective monitoring by generating network of queues at given output link.Packets associated with different sessions and originated from different hosts may be mixed up and queuing delay may become longer,depending on network segment state,buffering strategy,users’behavior among other factors.It is interesting to assimilate these stages of packets traveling through network segment to the concept of epidemic control.This paper proposes a SIR(Susceptible-Infected-Recovered)approach in modeling data packets transmission at a leaky bucket at peak hour.We focused our analysis on packets buffering and recovery strategy impact on segment forwarding performance in heavy load situation.Numerical results suggested adapting buffering strategy and packets recovery to enhance transmission and network overall performance.