Analysis methodology for flow-level evaluation of a hybrid mobile-sensor network

Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic

A Utility Proportional Fairness Radio Resource Block Allocation in Cellular Networks

This paper presents a radio resource block allocation optimization problem for cellular communications systems with users running delay-tolerant and real-time applications, generating elastic and inelastic traffic on the network and being modelled as logarithmic and sigmoidal utilities respectively. The optimization is cast under a utility proportional fairness framework aiming at maximizing the cellular systems utility whilst allocating users the resource blocks with an eye on application quality of service requirements and on the procedural temporal and computational efficiency. Ultimately, the sensitivity of the proposed modus operandi to the resource variations is investigated

A Price Selective Centralized Algorithm for Resource Allocation with Carrier Aggregation in LTE Cellular Networks

In this paper, we consider a resource allocation with carrier aggregation optimization problem in long term evolution (LTE) cellular networks. In our proposed model, users are running elastic or inelastic traffic. Each user equipment (UE) is assigned an application utility function based on the type of its application. Our objective is to allocate multiple carriers resources optimally among users in their coverage area while giving the user the ability to select one of the carriers to be its primary carrier and the others to be its secondary carriers. The UE's decision is based on the carrier price per unit bandwidth. We present a price selective centralized resource allocation with carrier aggregation algorithm to allocate multiple carriers resources optimally among users while providing a minimum price for the allocated resources. In addition, we analyze the convergence of the algorithm with different carriers rates. Finally, we present simulation results for the performance of the proposed algorithm.Comment: Submitted to IEE

Dynamic Bandwidth Allocation in Heterogeneous OFDMA-PONs Featuring Intelligent LTE-A Traffic Queuing

This work was supported by the ACCORDANCE project, through the 7th ICT Framework Programme. This is an Accepted Manuscript of an article accepted for publication in Journal of Lightwave Technology following peer review. © 2014 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A heterogeneous, optical/wireless dynamic bandwidth allocation framework is presented, exhibiting intelligent traffic queuing for practically controlling the quality-of-service (QoS) of mobile traffic, backhauled via orthogonal frequency division multiple access–PON (OFDMA-PON) networks. A converged data link layer is presented between long term evolution-advanced (LTE-A) and next-generation passive optical network (NGPON) topologies, extending beyond NGPON2. This is achieved by incorporating in a new protocol design, consistent mapping of LTE-A QCIs and OFDMA-PON queues. Novel inter-ONU algorithms have been developed, based on the distribution of weights to allocate subcarriers to both enhanced node B/optical network units (eNB/ONUs) and residential ONUs, sharing the same infrastructure. A weighted, intra-ONU scheduling mechanism is also introduced to control further the QoS across the network load. The inter and intra-ONU algorithms are both dynamic and adaptive, providing customized solutions to bandwidth allocation for different priority queues at different network traffic loads exhibiting practical fairness in bandwidth distribution. Therefore, middle and low priority packets are not unjustifiably deprived in favor of high priority packets at low network traffic loads. Still the protocol adaptability allows the high priority queues to automatically over perform when the traffic load has increased and the available bandwidth needs to be rationally redistributed. Computer simulations have confirmed that following the application of adaptive weights the fairness index of the new scheme (representing the achieved throughput for each queue), has improved across the traffic load to above 0.9. Packet delay reduction of more than 40ms has been recorded as a result for the low priority queues, while high priories still achieve sufficiently low packet delays in the range of 20 to 30msPeer reviewe

A Novel Packet Scheduling with Channel-Aware Algorithm for Multi-Service Flow in the LTE Network

Scheduling algorithm is one of many ways to increase system capacity and Quality of Service (QoS) in a telecommunication network. Designing a scheduling algorithm for a wireless network is challenging because its channel condition changes randomly according to the user's position. This paper investigated the performance of our proposed scheduling algorithm when managing multi-service flows in the downlink LTE network. The algorithm is the improvement of Proportional Fairness (PF) algorithm. The Extended-PF algorithm is a channel-aware scheduling algorithm that exploits users' channel condition information for calculating scheduling matrix in every scheduling process. Our simulation results showed that our proposed algorithm was able to provide better system's spectral efficiency

Segmented Learning for Class-of-Service Network Traffic Classification

Class-of-service (CoS) network traffic classification (NTC) classifies a group of similar traffic applications. The CoS classification is advantageous in resource scheduling for Internet service providers and avoids the necessity of remodelling. Our goal is to find a robust, lightweight, and fast-converging CoS classifier that uses fewer data in modelling and does not require specialized tools in feature extraction. The commonality of statistical features among the network flow segments motivates us to propose novel segmented learning that includes essential vector representation and a simple-segment method of classification. We represent the segmented traffic in the vector form using the EVR. Then, the segmented traffic is modelled for classification using random forest. Our solution's success relies on finding the optimal segment size and a minimum number of segments required in modelling. The solution is validated on multiple datasets for various CoS services, including virtual reality (VR). Significant findings of the research work are i) Synchronous services that require acknowledgment and request to continue communication are classified with 99% accuracy, ii) Initial 1,000 packets in any session are good enough to model a CoS traffic for promising results, and we therefore can quickly deploy a CoS classifier, and iii) Test results remain consistent even when trained on one dataset and tested on a different dataset. In summary, our solution is the first to propose segmentation learning NTC that uses fewer features to classify most CoS traffic with an accuracy of 99%. The implementation of our solution is available on GitHub.Comment: The paper is accepted to be appeared in IEEE GLOBECOM 202