Towards Viable Large Scale Heterogeneous Wireless Networks

We explore radio resource allocation and management issues related to a large-scale heterogeneous (hetnet) wireless system made up of several Radio Access Technologies (RATs) that collectively provide a unified wireless network to a diverse set of users through co-ordination managed by a centralized Global Resource Controller (GRC). We incorporate 3G cellular technologies HSPA and EVDO, 4G cellular technologies WiMAX and LTE, and WLAN technology Wi-Fi as the RATs in our hetnet wireless system. We assume that the user devices are either multi-modal or have one or more reconfigurable radios which makes it possible for each device to use any available RAT at any given time subject to resource-sharing agreements. For such a hetnet system where resource allocation is coordinated at a global level, characterizing the network performance in terms of various conflicting network efficiency objectives that takes costs associated with a network re-association operation into account largely remains an open problem. Also, all the studies to-date that try to characterize the network performance of a hetnet system do not account for RAT-specific implementation details and the management overhead associated with setting up a centralized control. We study the radio resource allocation problem and the implementation/management overhead issues associated with a hetnet system in two research phases. In the first phase, we develop cost models associated with network re-association in terms of increased power consumption and communication downtime taking into account various user device assumptions. Using these cost models in our problem formulations, the first phase focuses on resource allocation strategies where we use a high-level system modeling approach to study the achievable performance in terms of conflicting network efficiency measures of spectral efficiency, overall power consumption, and instantaneous and long-term fairness for each user in the hetnet system. Our main result from this phase of study suggests that the gain in spectral efficiency due to multi-access network diversity results in a tremendous increase in overall power consumption due to frequent re-associations required by user devices. We then develop a utility function-based optimization algorithm to characterize and achieve a desired tradeoff in terms of all four network efficiency measures of spectral efficiency, overall power consumption and instantaneous and long-term fairness. We show an increase in a multi-attribute system utility measure of up to 56.7% for our algorithm compared to other widely studied resource allocation algorithms including max-sum rate, proportional fairness, max-min fairness and min power. The second phase of our research study focuses on practical implementation issues including the overhead required to implement a centralized GRC solution in a hetnet system. Through detailed protocol level simulations performed in ns-2, we show an increase in spectral efficiency of up to 99% and an increase in instantaneous fairness of up to 28.5% for two sort-based user device-to-Access Point (AP)/Base Station (BS) association algorithms implemented at the GRC that aim to maximize system spectral efficiency and instantaneous fairness performance metrics respectively compared to a distributed solution where each user makes his/her own association decision. The efficiency increase for each respective attribute again results in a tremendous increase in power consumption of up to 650% and 794% for each respective algorithm implemented at the GRC compared to a distributed solution because of frequent re-associations

TCP-UB: A New Congestion Aware Transmission Control Protocol Variant

Transmission control protocol (TCP) is a connection oriented protocol for several types of distributed applications. TCP is reliable particularly for traditional fixed networks. With emergence of faster wireless networks, TCP has been performing poorly in its original format. The performance of TCP is affected due to assorted factors including congestion window, maximum packet size, retry limit, recovery mechanism, backup mechanism and mobility. To overcome deficiency of original TCP, Several modifications have been introduced to improve network quality. The mobility is a major hurdle in degrading the performance of mobile wireless networks. In this paper, we introduce and implement new TCP variant University of Bridgeport (UB) that combines the features of TCP Westwood and Vegas. We examine the performance of TCP-UB, Vegas and Westwood using different realistic scenarios. NS2 simulator demonstrates the stability of TCP-UB as compared with TCP Vegas and Westwood in highly congested networks from the mobility point of view

Load Balancing Hashing for Geographic Hash Tables

In this paper, we address the problem of balancing the network traffic load generated when querying a geographic hash table. State-of-the-art approaches can be used to improve load balancing by changing the underlying geo-routing protocol used to forward queries in the geographic hash table. However, this comes at the expense of considerably complicating the routing process, which no longer occurs along (near) straightline trajectories, but requires computing complex geometric transformations. Thus, current load balancing approaches are impractical in application scenarios where the nodes composing the geographic hash table have limited computational power, such as in most wireless sensor networks. In this paper, we propose a novel approach to solve the traffic load balancing problem in geographic hash tables: instead of changing the (near) straight-line geo-routing protocol used to send a query from the node issuing the query (the source) to the node managing the queried key (the destination), we propose to "reverse engineer" the hash function so that the resulting destination density, when combined with a given source density, yields a perfectly balanced load distribution. We first formally characterize the desired destination density as a solution of a complex integral equation. We then present explicit destination density functions (taken from the family of Beta distributions) yielding quasi-perfect load balancing under the assumption of uniformly distributed sources. Our theoretical results are derived under an infinite node density model. In order to prove practicality of our approach, we have performed extensive simulations resembling realistic wireless sensor network deployments showing the effectiveness of our approach in considerably improving load balancing. Differently from previous work, the load balancing technique proposed in this paper can be readily applied in geographic hash tables composed of computationally constrained nodes, as it is typically the case in wireless sensor networks

Benchmarking Wireless Network Protocols: Threat and Challenge Analysis of the AeroRP

To accommodate the unique conditions of mobile wireless networks, numerous protocols have been designed. Protocols are initially tested through simulation software, but often under non-realistic conditions, using simple or even ideal wireless environments not usually found in the real world. Without challenges and channel impairments, such simulations cannot accurately determine the advantages and disadvantages of the protocol nor can a reliable comparison be made between the performance of any two protocols. New protocols must be tested in a manner consistent with legacy protocols so they can be accurately compared and improved upon. The contributions of this thesis are a set of models that can create more realistic and challenging simulations, including a 3-D implementation of the Gauss-Markov mobility model, and a set of benchmarks that can be used to test the strengths and weaknesses of wireless routing protocols. These benchmarks are then applied to several MANET protocols including AODV, DSR, OLSR, DSDV, and AeroRP that is part of the Aero protocol stack developed at The University of Kansas. AeroRP outperforms the traditional MANET routing protocols in benchmarks that involve either highly-dynamic networks or disruptions in connectivity

Reducing energy consumption in mobile ad-hoc sensor networks

PhD ThesisRecent rapid development of wireless communication technologies and portable mobile devices such as tablets, smartphones and wireless sensors bring the best out of mobile computing, particularly Mobile Ad-hoc Sensor Networks (MASNETs). MASNETs are types of Mobile Ad-hoc Networks (MANETs) that are designed to consider energy in mind because they have severe resource constraints due to their lack of processing power, limited memory, and bandwidth as in Wireless Sensor Networks (WSNs). Hence, they have the characteristics, requirements, and limitations of both MANETs and WSNs. There are many potential applications of MASNETs such as a real-time target tracking and an ocean temperature monitoring. In these applications, mobility is the fundamental characteristic of the sensor nodes, and it poses many challenges to the routing algorithm. One of the greatest challenge is to provide a routing algorithm that is capable of dynamically changing its topology in the mobile environment with minimal consumption of energy. In MASNETs, the main reason of the topology change is because of the movement of mobile sensor nodes and not the node failure due to energy depletion. Since these sensor nodes are limited in power supply and have low radio frequency coverage, they easily lose their connection with neighbours, and face diffi culties in updating their routing tables. The switching process from one coverage area to another consumes more energy. This network must be able to adaptively alter the routing paths to minimize the effects of variable wireless link quality, topological changes, and transmission power levels on energy consumption of the network. Hence, nodes prefer to use as little transmission power as necessary and transmit control packets as infrequently as possible in energy constrained MASNETs. Therefore, in this thesis we propose a new dynamic energy-aware routing algorithm based on the trans- mission power control (TPC). This method effectively decreases the average percentage of packet loss and reduces the average total energy consumption which indirectly pro- long the network lifetime of MASNETs. To validate the proposed protocol, we ran the simulation on the Avrora simulator and varied speed, density, and route update interval of mobile nodes. Finally, the performance of the proposed routing algorithm was measured and compared against the basic Ad-hoc On-demand Distance Vector (AODV) routing algorithm in MASNETs.The Ministry of Education of Malaysia: The Universiti Malaysia Sarawak

An Intelligent Mobility Prediction Scheme for Location-Based Service over Cellular Communications Network

One of the trickiest challenges introduced by cellular communications networks is mobility prediction for Location Based-Services (LBSs). Hence, an accurate and efficient mobility prediction technique is particularly needed for these networks. The mobility prediction technique incurs overheads on the transmission process. These overheads affect properties of the cellular communications network such as delay, denial of services, manual filtering and bandwidth. The main goal of this research is to enhance a mobility prediction scheme in cellular communications networks through three phases. Firstly, current mobility prediction techniques will be investigated. Secondly, innovation and examination of new mobility prediction techniques will be based on three hypothesises that are suitable for cellular communications network and mobile user (MU) resources with low computation cost and high prediction success rate without using MU resources in the prediction process. Thirdly, a new mobility prediction scheme will be generated that is based on different levels of mobility prediction. In this thesis, a new mobility prediction scheme for LBSs is proposed. It could be considered as a combination of the cell and routing area (RA) prediction levels. For cell level prediction, most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the New Markov-Based Mobility Prediction (NMMP) and Prediction Location Model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression and insufficient accuracy. In this thesis, Location Prediction based on a Sector Snapshot (LPSS) is introduced, which is based on a Novel Cell Splitting Algorithm (NCPA). This algorithm is implemented in a micro cell in parallel with the new prediction technique. The LPSS technique, compared with two classic prediction techniques and the experimental results, shows the effectiveness and robustness of the new splitting algorithm and prediction technique. In the cell side, the proposed approach reduces the complexity cost and prevents the cell level prediction technique from performing in time slots that are too close. For these reasons, the RA avoids cell-side problems. This research discusses a New Routing Area Displacement Prediction for Location-Based Services (NRADP) which is based on developed Ant Colony Optimization (ACO). The NRADP, compared with Mobility Prediction based on an Ant System (MPAS) and the experimental results, shows the effectiveness, higher prediction rate, reduced search stagnation ratio, and reduced computation cost of the new prediction technique

Performance Evaluation of Ad Hoc Routing in a Swarm of Autonomous Aerial Vehicles

This thesis investigates the performance of three mobile ad hoc routing protocols in the context of a swarm of autonomous unmanned aerial vehicles (UAVs). It is proposed that a wireless network of nodes having an average of 5.1774 log n neighbors, where n is the total number of nodes in the network, has a high probability of having no partitions. By decreasing transmission range while ensuring network connectivity, and implementing multi-hop routing between nodes, spatial multiplexing is exploited whereby multiple pairs of nodes simultaneously transmit on the same channel. The proposal is evaluated using the Greedy Perimeter Stateless Routing (GPSR), Optimized Link State Routing (OLSR), and Ad hoc On-demand Distance Vector (AODV) routing protocols in the context of a swarm of UAVs using the OPNET network simulation tool. The first-known implementation of GPSR in OPNET is constructed, and routing performance is observed when routing protocol, number of nodes, transmission range, and traffic workload are varied. Performance is evaluated based on proportion of packets successfully delivered, average packet hop count, and average end-to-end delay of packets received. Results indicate that the routing protocol choice has a significant impact on routing performance. While GPSR successfully delivers 50% more packets than OLSR, and experiences a 53% smaller end-to-end delay than AODV when routing packets in a swarm of UAVs, increasing transmission range and using direct transmission to destination nodes with no routing results in a level of performance not achieved using any of the routing protocols evaluated

Recommendation based trust model with an effective defence scheme for MANETs

YesThe reliability of delivering packets through multi-hop intermediate nodes is a significant issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish connections to form the MANET, which may include selfish and misbehaving nodes. Recommendation based trust management has been proposed in the literature as a mechanism to filter out the misbehaving nodes while searching for a packet delivery route. However, building a trust model that relies on the recommendations from other nodes in the network is vulnerable to the possible dishonest behaviour, such as bad-mouthing, ballot-stuffing, and collusion, of the recommending nodes. . This paper investigates the problems of attacks posed by misbehaving nodes while propagating recommendations in the existing trust models. We propose a recommendation based trust model with a defence scheme that utilises clustering technique to dynamically filter attacks related to dishonest recommendations within certain time based on number of interactions, compatibility of information and node closeness. The model is empirically tested in several mobile and disconnected topologies in which nodes experience changes in their neighbourhoods and consequently face frequent route changes. The empirical analysis demonstrates robustness and accuracy of the trust model in a dynamic MANET environment