Reema Sharma

Probabilistic Prediction based Scheduling for Delay Sensitive Traffic in Internet of Things

This paper proposes a probabilistic prediction based approach for providing Quality of Service (QoS) to delay sensitive traffic for Internet of Things (IoT). A joint packet scheduling and dynamic bandwidth allocation scheme is proposed to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping the waiting time of other services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services by avoiding distribution of excess resources for high priority services and yet guaranteeing the services for it. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loading. The results show the improved performance with respect to waiting time for scheduling high priority packets and simultaneously keeping tolerable limits for waiting time and packet loss for other services. Crown Copyright (C) 2015 Published by Elsevier B.V.

QoS-Alert Markov Chain Based Scheduling Scheme in Internet of Things

Guaranteeing quality of service (QoS) to transmit real time applications which are delay sensitive is of utmost importance in Internet of Things (IoT) environment. This paper presents a dynamic Markov Chain based scheduling scheme for ensuring QoS for the delay sensitive traffic in IoT. The traffic is classified into prioritized and non- prioritized traffic. By estimating previous bandwidth allocated to prioritized traffic and the amount of decrease/increase in probability of average queue length of prioritized packets in consecutive cycles, the scheduler dynamically adjusts the percentage of link bandwidth allocated to it in each cycle. This helps in providing guaranteed services to real time traffic in IoT applications and simultaneously provide better throughput for non real time traffic as well. The proposed QoS- alert scheduling mechanism is able to optimize the desired performance in IoT network. For different experiments the simulation is performed which verifies and satisfies the blocking probability requirements of prioritized traffic for IoT data.

Design and development of non data aided estimation algorithm for carrier frequency-offset and I/Q imbalancing in OFDM-based systems

Orthogonal Frequency Division Multiplexing (OFDM) systems are particularly sensitive to carrier frequency offset (CFO) and Inphase and Quadrature (I/Q) imbalance. These parameters degrade the performance of OFDM-based system as they destroy the orthogonality between sub-carriers. In this paper, we designed an estimation algorithm which is based on non data aided technique for the CFO and I/Q imbalance by taking advantage of the inherent orthogonal structure in the OFDM signal. We particularly analyze the different standards of 802.11, the wireless local area network (WLAN) that are OFDM based to evaluate the performance of this algorithm. The simulation results show the improvement of new estimator over the existing one in the presence of I/Q Imbalance.

Packet Scheduling Scheme to Guarantee QoS in Internet of Things

In this paper, a new prediction based dynamic scheduling mechanism is proposed to ensure quality of service especially in internet of things (IoT) by dynamically allocating bandwidth. The scheduling scheme is analyzed for two different applications: (1) to accommodate various streaming data of IoT applications or for medical applications. Traffic is segregated based on different traffic characteristics such as bit rate, packet loss rate and tolerable delay into different classes and they are prioritized based on these characteristics; and (2) to consider continuous long time data from all lightweight devices like sensors. The algorithm allocates bandwidth such that its utilization can be optimized for different applications. The scheduler decision is divided into two steps: (1) calculating average increase in queue length of high priority and medium priority services at current time slot from the previous time slot and, (2) adding these values to previous weight values for corresponding services and multiplying with a coefficient. The performance is carried out under different system loading and scenarios. The results illustrate the improvement of the advised scheduler with respect to end to end delay distributions, packet drop and end to end jitter values.

Performance of New Dynamic Benefit-Weighted Scheduling Scheme in DiffServ Networks

In this paper, we design a new dynamic packet scheduling scheme suitable for differentiated service (DiffServ) network. Designed dynamic benefit weighted scheduling (DBWS) uses a dynamic weighted computation scheme loosely based on weighted round robin (WRR) policy. It predicts the weight required by expedited forwarding (EF) service for the current time slot (t) based on two criteria; (i) previous weight allocated to it at time (t-1), and (ii) the average increase in the queue length of EF buffer. This prediction provides smooth bandwidth allocation to all the services by avoiding overbooking of resources for EF service and still providing guaranteed services for it. The performance is analyzed for various scenarios at high, medium and low traffic conditions. The results show that packet loss is minimized, end to end delay is minimized and jitter is reduced and therefore meet quality of service (QoS) requirement of a network.

Markov Chain Based Priority Queueing Model for Packet Scheduling and Bandwidth Allocation

This paper considers classification of diverse traffic types in Internet of Things (IoT) based on importance of data rate, packet size and proposes a priority-based probabilistic packet scheduling strategy for efficient packet transmission. Reduction of peak resource usage, dynamic control of service rate corresponding to arrival rate and QoS buffer management are few main factors considered to develop this strategy. By calculating percentage of link bandwidth required for prioritized traffic in each cycle, we provide quality of service (QoS) to real time traffic in IoT and non-IoT applications. Different experiments including MPEG traffic traces and Poisson traffic are conducted to verify the proposed scheduler. Also, performance of scheduler for both IoT and Non-IoT applications is compared for different data rates. We observe that the proposed packet scheduler satisfies QoS requirements for both IoT and non-IoT traffic.

Dynamic benefit-weighted scheduling scheme in multi service networks

This paper proposes a new dynamic packet scheduling scheme which guarantees the delay and jitter properties of differentiated services (DiffServ) network for both real time and non-real time traffics. The proposed dynamic packet scheduling algorithm uses a new weighted computation scheme known as dynamic benefit weighted scheduling (DB-WS) which is loosely based on weighted round robin (WRR) or fair queuing policy. The novelty of this scheduler is that it predicts the weight required by expedited forwarding (EF) service for current time slot (t) based on two factors: (i) previous weight allocated to it at time slot (t-1), and (ii) average increase in weights of EF traffic in consecutive time slots. This prediction provides smoother and balanced bandwidth allocation to EF, assured forwarding (AF) and best effort (BE) packets by not allocating all the resources to EF and also ensuring minimal packet losses for EF service. Adopting such a dynamic resource allocation effectively achieves reduction in packet loss, end to end delay and delay jitter. The algorithm is tested with different data rates and found to outperform other existing methods in terms of packet loss and end to end delay.

Waiting Time Analysis for Delay Sensitive Traffic in Internet of Things

In this paper, waiting time analysis for the delay sensitive traffic especially in Internet of things (IoT) is performed. The analysis is based on probabilistic prediction approach for providing Quality of Service (QoS). A dynamic packet scheduling scheme is considered to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping medium and low priority services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loadings. The results show the improved performance with respect to waiting time for scheduling high priority packets.

Carrier frequency offset with I/Q imbalance analysis of fifth generation WiFi

The performance of the Orthogonal Frequency Division Multiplexing (OFDM) based systems degrades especially being sensitive to carrier frequency offset (CFO) and inphase and quadrature (I/Q) imbalance which destroys orthogonality between subcarriers. The IEEE 802.11ac (fifth generation) wireless local area network (WLAN) standard uses OFDM equally spaced subcarriers to transmit data, and the number of subcarriers signal depend on the bandwidth. In this paper, we investigate the system behaviour considering CFO and I/Q imbalance impairments. Our studies focus on two important non data aided algorithms. The results of analysis are presented for different subcarriers in combination with modulation and throughput.

New dynamic QoS routing algorithm for optical networks based on MPLS with delay and Bandwidth as constraints

Bandwidth and Delay are quality parameters that can be guaranteed for new connections that are offered to the network by finding a suitable path in the network. Finding such a suitable path is the task of QoS routing techniques developed for IP Optical networks based on Multiprotocol Label Switching (MPLS). In this paper we focus on dynamic routing of Bandwidth (1Mbps/link) and delay (1ms/link) guaranteed flows in optical networks based on label forwarding techniques. We are presenting simulation results to compare the performances of Optical Networks with Wired networks under wide range of topologies and system parameters. The simulation results show that considering an optical fibre as link, the call blocking ratio is reduced by 2.4% as compared to a non optical link in same topological environment.