Toktam Mahmoodi

Cross-Layer Optimization to Maximize Fairness Among TCP Flows of Different TCP Flavors

A significant body of recent research has analyzed the problematic behavior of TCP over wireless links, and a plethora of modifications to TCP have been proposed in order to increase its performance in such contexts. Two schools of thought have emerged: the first proposes changes to the end-to- end protocol, while the second explores the potential to enhance lower layers as a means to improve the end-to-end performance of TCP. This paper focuses on the latter, and in contrast to most research in this area, which thus-far has concentrated on a single TCP flavor, examines the case where different TCP flavors are competing over a wireless link. To this end, we present and assess a cross-layer solution that involves the adaptation of lower layer characteristics (i.e., the coding rate) based on the detected TCP flavor, in order to maximize the fairness among TCP flows. Through extensive numerical investigations, we show that the proposed scheme considerably improves the fairness over wireless links among different TCP flavors. Our approach also has a minimal effect on the aggregate throughput of the TCP flows, and in cases where the packet error rate is very low, has a small positive effect on throughput.

Programmable policies for data offloading in LTE network

Mobile data offloading on smaller cells such as Wi-Fi comes as a natural solution to boost cellular networks capacity and keep up with the rapid increase of mobile data traffic demand. In this paper, we propose an offloading mechanism through the abstraction of Software-defined Networking (SDN) in the mobile backhaul to provide programmable offloading policy derivation that are aware of users and applications as well as the condition of wireless network. The proposed mechanism considers the real-time network condition to derive the offloading policies and efficiently accommodate the traffic in both LTE and Wi-Fi networks. Numerical results prove that the proposed approach can significantly improves dropping rate of the incoming traffic with using more real-time and dynamic decisions for offloading.

Energy-aware routing in the Cognitive Packet Network

An energy aware routing protocol (EARP) is proposed to minimise a performance metric that combines the total consumed power in the network and the QoS that is specified for the flows. The algorithm uses source routing based on the functionalities provided by the Cognitive Packet Network (CPN), running autonomously at each input node to the network based on smart packets which gather relevant information throughout the network using reinforcement learning at each of the intermediate nodes. Measurements on an experimental test-bed that uses EARP are presented and they indicate that it offers a reduction in power consumption, as compared to a purely QoS driven approach, and also respects the requested QoS level.

Traffic Jam: Handling the Increasing Volume of Mobile Data Traffic

Todays mobile operators face significant challenges with handling the ever increasing volume of mobile data traffic. With new mobile communication standards, the mobile backhaul architecture has a clear split of a packet-only data plane and a management plane. Although this new backhaul architecture yields to easier management, we find that this architecture can be improved further by applying the principles of software-defined networking (SDN). SDN allows for better evolvability of the data plane without depending on a slew of management or control protocols, allows for centralized control of the overall infrastructure, and allows for a richer feature set based on its programmable nature. This article investigates the redesign and illustrates its potential with mobility management as an example.

Energy Efficient Resource Allocation Strategy for Cloud Data Centres

Cloud computing data centres are emerging as new candidates for replacing traditional data centres. Cloud data centres are growing rapidly in both number and capacity to meet the increasing demands for highly-responsive computing and massive storage. Making the data centre more energy efficient is a necessary task. In this paper, we focus on the organisation’s internal Infrastructure as a Service (IaaS) data centre type. An internal IaaS cloud data centre has many distinguished features with heterogeneous hardware, single application, stable load distribution, lived load migration and highly automated administration. This paper will propose a way of saving energy for IaaS cloud data centre considering all stated constraints. The basic idea is rearranging the allocation in a way that saving energy. The simulation results show the efficiency of the method.

Enabling the IoT Machine Age With 5G: Machine-Type Multicast Services for Innovative Real-Time Applications

The Internet of Things (IoT) will shortly be undergoing a major transformation from a sensor-driven paradigm to one that is heavily complemented by actuators, drones, and robots. The real-time situational awareness of such active systems requires sensed data to be transmitted in the uplink to edge-cloud, processed, and control instructions transmitted in the downlink. Since many of these applications will be mission critical, the most suitable connectivity family will be cellular due to the availability of licensed spectrum able to protect the offered communications service. However, while much focus in the past was on the uplink of machine-type communications, little attention has been paid to the end-to-end reliability, latency, and energy consumption comprising both up and downlinks. To address this gap, in this paper, we focus on the definition, design, and analysis of machine-type multicast service (MtMS). We discuss the different procedures that need to be redesigned for MtMS and we derive the most appropriate design drivers by analyzing different performance indicators, such as scalability, reliability, latency, and energy consumption. We also discuss the open issues to be considered in future research aimed at enhancing the capabilities of MtMS to support a wide variety of 5G IoT use cases.

Cross-Layer Design to Improve Wireless TCP Performance with Link-Layer Adaptation

Transmission control protocol (TCP), the almost universally used reliable transport protocol in the Internet, has been engineered to perform well in wired networks where packet loss is mainly due to congestion. TCP throughput, however, degrades over wireless links, which are characterized by a high and greatly varying bit error rate and by intermittent connectivity. Over such wireless links, the performance achieved by TCP can be improved through the use of cross-layer algorithms at the link-level, which interact with the TCP state machine. In this paper, a TCP-aware dynamic ARQ algorithm is therefore proposed, which utilizes TCP timing information to prioritize ARQ packet retransmissions. Numerical investigation of the proposed algorithm demonstrates the performance improvements that can be attained through this approach, in comparison with TCP-agnostic link-layer approaches.

Balancing Sum Rate and TCP Throughput in OFDMA Based Wireless Networks

Abstract-In this paper, we propose a dynamic OFDMA based subcarrier/power allocation scheme, which aims to balance the aggregate rate and the achieved TCP throughput of competing TCP flows. The proposed allocation utilizes the theoretical TCP throughput which can be accomplished in the end-to-end path. In doing so, the TCP aware scheme attempts to minimize the gap between the allocated rate and the theoretical upper bound under the system constraints. Such a technique can be of significant importance since due to its popularity, TCP is commonly used for streaming video or other ultimedia applications. Numerical investigations reveal that the proposed approach, provides more balance towards the TCP throughput, and under some considerations significantly increase the fairness among competing TCP flows over end-to-end paths of different characteristics. In addition to that, it also manages to avoid starvation of TCP flows with poor channel conditions.

Softwarization and Virtualization in 5G Networks for Smart Cities

Smart cities are one of the foreseeable mission-critical hybrid networks connecting machines and humans to provide various public services through highly reliable, ultra-low latency and broadband communications. It is known that the next generation mobile networks, a.k.a 5G networks, should address requirements of such hybrid network inherently. Among the main features of 5G networks, therefore, are cognition and programmability that allow for addressing different needs. These features are so far discussed with the introduction of softwarization and virtualization technologies. In this paper, we briefly discuss how the two technologies enable use of 5G in the smart cities and allow for multiple tenants to share a common physical infrastructure. We further describe an example use case through which such multiple tenant environment can be designed.

On the Feasibility of MAC and PHY Split in Cloud RAN

Splitting functionalities of radio access network (RAN) and cloudiamp;#64257;cation of such functionalities is considered as oneofthekeyenablersofthenextgenerationmobileandwireless networking, i.e. 5G, and is often referred to as software-deamp;#64257;ned RAN, virtualized RAN or Cloud RAN. Deamp;#64257;ning the splitting point, and maintaining the tight interaction between different functionalities in the RAN is, however, critical. Success of such cloudiamp;#64257;cation depends on the availability of high speed fronthaul, while high speed fronthauling is costly. In this paper we experiment splitting MAC and PHY layer with fronthauling through Ethernet that allows using commodity and low-cost industry standard equipment. We examine the effect of packetization on latency, and study the pros and cons of splitting MAC and PHY layer, within a hardware-based testbed.