Achieving Relative Differentiated Services Using Proportional Probabilistic Priority Scheduling on Network Processor

The assured forwarding per hop behavior (AF PHB) has been devised by the IETF differentiated services (DiffServ) working group to provide drop level differentiation. This paper shows, quite surprisingly, that a standard AF PHB class is semantically capable of supporting per flow admission control. This is obtained by adopting the AF PHB as the core router forwarding mechanism in conjunction with an end point admission control mechanism running at the network edges. Our work appears to prove that the extent of the AF PHB can be larger than was originally expected, since it can support an admission control mechanism, which is deemed necessary in recent RFCs to offer QoS aware services. An interesting related issue is whether the expedited forwarding PHB, devised to support flows with strict delay requirements, and based on a single DSCP tag, should be redesigned as a PHB class to comply with end point admission control. Preliminary performance results show that, under suitable assumptions, our scheme can provide as much as hard QOS guarantees (see Bianchi, G. et al., IEEE Globecom, 2001; http://drake.diei.unipg.it/netweb/GRIP/sub -/tech/sub -/rep.pdf).

Most of the existing packet scheduling mechanisms of the wireless sensor network use First Come First Served (FCFS) non pre emptive priority and pre emptive priority scheduling algorithms. The above algorithms have high processing overhead and also long end-to-end data transmission delay. In FCFS concept the data packet which is entering the node first will go out first from the node, and the packet which will enter last will leave at last. But in FCFS scheduling of real time data packets coming to the node have to wait for a long time period.In non pre emptive priority scheduling algorithm there is starvation of real time data packets because once the processor enters the running state, it will not allow remove until it is completed, so there is starvation of real time data packets. In pre emptive scheduling, starvation of non real time data packets, due to continuous arrival of real time data. Therefore the data packets are to be schedule in multilevel queue. But the multilevel queue scheduling scheme is not suitable for dynamic inputs, and hence the scheme is designed for dynamically change in the inputs. The Dynamic Multilevel Priority (DMP) packet scheduling is the scheme for dynamically changes in the inputs. In this scheme each node except the last level of the virtual hierarchy in the zone based topology of wireless sensor network has three levels of priority queues. Real time data packets are placed into highest priority queue and can preempt the data packets in the other queues. Non real time data packets are placed into other two queues based on threshold of their estimated processing time. The leaf node have two queues, one for real time data packet and another for non real time data packet since they do not receive data from other nodes and thus reduces end to end delay. This scheme reduces the average waiting time and end-to -end delay of data packets.

With the applications of Internet of Things (IoT) for smart cities, the real-time performance for a large number of network packets is facing serious challenge. Thus, how to improve the emergency response has become a critical issue. However, traditional packet scheduling algorithms cannot meet the requirements of the large-scale IoT system for smart cities. To address this shortcoming, this paper proposes EARS, an efficient data-emergency-aware packet scheduling scheme for smart cities. EARS describes the packet emergency information with the packet priority and deadline. Each source node informs the destination node of the packet emergency information before sending the packets. The destination node determines the packet scheduling sequence and processing sequence according to emergency information. Moreover, this paper compares EARS with a first-come, first-served, multilevel queue algorithm and a dynamic multilevel priority packet scheduling algorithm. Simulation results show that EARS outperforms these previous scheduling algorithms in terms of packet loss rate, average packet waiting time, and average packet end-to-end delay.

This paper presents the performance evaluation of per-hop forwarding behavior in the differentiated services Internet. Both the expedited forwarding and the assured forwarding behaviors are observed and investigated in terms of packet delay and packet drop rate. This investigation was carried out using Queen's University IP Simulator v2.0 (QUIPS-II). A significant amount of results have been obtained under various parameter settings. The results show that the Diffserv per-hop forwarding mechanisms can provide good service differentiation on the Internet.

Packet collision is the primary source of unnecessary energy usage in wireless sensor networks (WSNs). To address this issue, the advanced packet scheduling algorithm is presented. In real-time WSNs, some packet scheduling techniques can also affect and delay data transmission. Efficient packet scheduling is vital for minimizing energy consumption and data transmission delay in WSNs. It is crucial because it guarantees the fair and timely distribution of various kinds of data packets according to their priorities. Node will directly transmit the packet to its destination based on its priority. However, current approaches like first come first serve (FCFS) schedulers often result in significant latency, hindering timely data delivery to base stations (BS). To address this, we propose a novel dynamic multi-level round search mayfly optimizer-based priority packet scheduling technique (MRSMOPS). This technique utilizes a traffic-aware-weighted queue (TAWQ) model to schedule tasks based on priority, optimizing transmission slots for flowing packets. Our objective is to reduce overall transmission completion time while adhering to delay limits and energy budgets. By integrating the newly developed MRSMOPS method, the efficiency of packet scheduling is enhanced in WSNs. The proposed algorithm has demonstrated significant improvements in performance metrics, achieving a 15% reduction in packet delay and a 10% enhancement in energy efficiency compared to existing methods.

The efficiency of the emerging smart power grid infrastructure critically depends on the ability of the communication network to deliver real-time energy prices to the consumers. This paper's contribution is twofold. First, it derives the relevant Quality of Service (QoS) communication requirements and proposes the corresponding overall performance criterion for the communication network, which quantifies the negative effect of delaying energy pricing information on the grid operations. Second, this paper demonstrates that the conventional Network Utility Maximization (NUM) based cross-layer optimization framework can be enhanced to incorporate the specific requirements of the smart power grid infrastructure. The conventional NUM based cross-layer network optimization balances tradeoffs between bandwidth requirements of multiple users, given limited network resources. The proposed enhanced NUM also allows the system to balance user requirements for (a) communication reliability by taking advantage of multipath routing in presence of network outages, and (b) communication delays by taking advantage of priority packet scheduling. Future research should quantify advantages of the proposed robust and QoS-aware NUM as compared to the conventional NUM for specific operation scenarios of the smart power grid infrastructure.

With the widespread applications of Internet of Things (IoT), the emergency response performance for large-scale network packets is facing serious challenge, especially for renewable distributed energy resources monitoring in a smart grid. Therefore, how to improve the real-time performance of the emergency data packets has been a critical issue. Traditional packet scheduling schemes and topology optimization strategies are not suitable for a large-scale IoT-based smart grid. To address this problem, this paper proposes a new packet scheduling scheme named LOES, which first combines the priority-based packet scheduling scheme with local optimization. We exchange local geographic information to reduce the hop counts and distance between distributed source nodes and sink nodes. Each destination node determines the packet scheduling sequence according to the received emergency information. Finally, we compare LOES with first come first serve, multilevel scheme, and dynamic multilevel priority packet scheduling scheme using packet loss rate, packet waiting time, and average packet end-to-end delay as metrics. The simulation results show that LOES outperforms these previous scheduling schemes.