Some research projects available in ANRG:

Detection of Anomalous Variations in Dynamic Networks

The intranet is fast becoming the preferred enterprise solution for delivering interoperable communications for internal information exchange. The term intranet implies a private data network that makes use of communication protocols and services of the Internet, such as the TCP/IP protocol suite. Over recent years these data networks have experienced significant growth in size and complexity resulting in an increase in frequency, type and severity of network problems. To ensure early detection and identification of these problems better network management techniques must be employed. In the management of large enterprise intranets (data networks), it becomes difficult to detect and identify causes of abnormal change in traffic distributions when the underlying logical topology is dynamic. Network management techniques use statistical trending methods and visualization tools to monitor network performance. These techniques are good for managing traffic but can be inadequate when networks are very dynamic (physical and logical structures of time-varying nature added to traffic variations). This project aims to complement these existing techniques with suitable metrics that allow the automatic detection of significant change within a network and alert operators to when and where the change occurred. Applications are manifold: discovery and prediction of network faults and abnormalities, overload, congestion, hotspots, etc. Possible topics: network reconstruction out of routing tables, where to put (a given number of) probes in order to get maximal coverage of network abnormalities, how does network monitoring depend on network protocols? If one has a time series of network transaction files, can one not monitor network (when?) and not loose too much information? What to do if there are “holes” in time series or in network(s)? In other words: Can a network be monitored without full knowledge of the entire network (network inference?)
Contact: Prof. Albert Zomaya

Using (mobile) Agents in Sensor Networks

Recently, a new approach for learning features of a domain of interest has been proposed. The main characteristic of the novel approach is the fact that global information about the domain is obtained by combining in some clever way local information gathered by independent agents. In fact, for a large number of practically-relevant domains the following paradigm can be used: (1) a large number of agents, each with a specific mandate is being sent into the domain, (2) each agent learns a given characteristic or feature of the domain, (3) a subset of the agents is recovered and debriefed. Somewhat surprisingly, for many domains it is possibly to recover a strict subset of the agents and still obtain “full” knowledge about the domain. It would be very useful to implement strategies for 1-3 above for a number of particular domains arising in various practical applications. Of a particular interest is the area of mobile computing and sensor networks.
Contact: Prof. Albert Zomaya

Scheduling in Grid Computing and Multi-Server HPC Environments

Grid systems are gaining a lot of momentum as the next generation of systems that will provide high performance capabilities to a wide range of applications. These applications will have different, and sometimes conflicting, requirements. This will necessitate the development of more flexible scheduling techniques. Another factor which is detrimental to the performance of such grids is the dynamic nature of such combination of heterogeneous resources that are, for most of the time, located in disparate locations. In addition, the availability of resources (e.g. computational, storage, etc) for some of the time does not mean that such resources will be available all the time. Such conditions will add more complexity to the design of grid schedulers. This also suggests the need to suites of schedulers that can be used in different operating scenarios. This project deals with the study and development of a variety of scheduling scenarios and algorithms that can help in achieving the ultimate goal of furthering our understanding of grid scheduling.
Contact: Prof. Albert Zomaya

Constructing Comparative Maps for the Aggregation of Genetic Information

Comparative maps are powerful techniques for the aggregation of genetic information about related organisms, for inferring phylogenetic relationships, and for examining hypotheses about the evolution of gene families and the functional significance of orthologous genes. The construction of gene maps is a very difficult task and the compilation of such maps across multiple species is even harder. This work will attempt to automate this process by using meta-heuristics (e.g. genetic algorithms, Tabu search, etc) that are also parallelizable in nature. This makes them suitable candidates for parallel implementations and as results extends their applicability to massive data sets and a wider range of gene families.
Contact: Prof. Albert Zomaya

Algorithms for Protein Folding

Protein folding algorithms aim to understand how the amino acid sequence of a protein determines its unique native conformation. Experimental methods, such as X-ray crystallography, determine the native structure of a protein with a great accuracy. However, there is need for more powerful and “intelligent” optimization algorithms to simulate the process of folding. This project deals with the development of parallel optimization algorithms based on traditional and artificial life paradigms to solve protein-folding problems. These techniques are deployed onto grid-enabled platforms to facilitate the execution of these compute- and data-intensive algorithms.
Contact: Prof. Albert Zomaya

Modelling of Complex Metabolic Pathways Genomics and Proteomics

Complex multicellular organisms contain large genomes in which each structural gene is associated with at least one regulatory element and each regulatory element integrates the activity of at least two other genes. The nature of such regulation started to be understood from the analysis of small prokaryotic regulation subsystems and the current picture indicates that the webs that shape cellular behaviour are very complex. This project deals with the development of algorithms and tools that can be used to analyse metabolic networks based on heuristics and meta-heuristics.
Contact: Prof. Albert Zomaya

Parallel Algorithms for Building Comparative Gene Maps

Comparative maps are powerful techniques for the aggregation of genetic information about related organisms, for inferring phylogenetic relationships, and for examining hypotheses about the evolution of gene families and the functional significance of orthologous genes. The construction of gene maps is a very difficult task and the compilation of such maps across multiple species is even harder. This work will attempt to automate this process by using meta-heuristics (e.g., genetic algorithms, Tabu search, swarm algorithms, etc) that are also parallelizable in nature. This makes such techniques suitable candidates for parallel implementations and as a result extends their applicability to massive data sets and a wider range of gene families.

Healing and Self-Repair in Grid Computing Systems

As Grids receive more acceptance with time there will be a need to endow such systems with capabilities that make them capable of operating in disaster scenarios. What makes this problem very complex is the heterogeneous nature of Grid environments that could be made up of hundreds or thousands of components (computers, databases, etc). In addition, a user in one location might not be able to have control over other parts of the grid. So it is rather logical that there is a need for “smart” algorithms (protocols) that can achieve such an acceptable level of fault-tolerance and account for a variety of disaster recovery scenarios.

Scheduling Communications in Cluster Computing Systems

Clusters of commodity computer systems have become the fastest growing choice for building cost-effective high-performance parallel computing platforms. The rapid advancement of computer architectures and high-speed interconnects have facilitated many successful deployments of this type of clusters. Researchers in previous studies have reported that, the cluster interconnect significantly impacts the performance of parallel applications. High-speed interconnects not only unveil the potential performance of the cluster, but also allow clusters to achieve better performance/cost ratio than clusters with traditional local area networks. Towards this end, this project aims to study the how computations and communications influence the performance of such systems. Applications tend to range from the compute-intensive to the communication-intensive and an understanding of such applications and how they map efficiently onto clusters is important.

Organising Protocols for Wireless Sensor Networks

In a wireless sensor network, energy conservation is the primary design goal. Research shows that in a low-energy radio network, the energy consumed by receiving and listening (attempting to receive) messages is of the same order of magnitude as transmitting them. The most efficient way to save energy is keeping sensor nodes turned off as long as possible. These sleeping-or-awaking nodes need the capabilities of self-organisation and re-organisation to adapt to dynamic environment and network settings. This work address issues of energy efficient self-organisation in sensor networks. The work also deals with situations in which the network needs to efficiently adapt in catastrophe scenarios by maintaining reasonable energy levels that keep the network active for the longest period of time.

Cross Layer Optimisation for Wireless Sensor Networks

Deploying sensor nodes with rather limited power source is a challenging task that requires a new design approach. The design objective is to optimize the network lifetime and energy efficiency. One such design involves a cross-layer view between the physical and MAC layer, where the access decision is better informed by the current channel state and the associated channel predictions. We could look at other possible cross-layer optimisation too.

Study of In-Network Processing in Wireless Sensor Networks

Sensor networks are distributed event-based systems that differ from traditional communication networks in several ways: sensor networks have severe energy constraints, redundant low-rate data, and many-to-one flows. Data centric mechanisms that perform in-network aggregation of data are needed in this setting for energy-efficient information flow. In this project, we will investigate about data-centric routing with in-network processing. Accordingly, we will propose and develop a suitable in-network processing framework that integrates well a suitable routing protocol in an energy efficient way.

Distributed Localisation for Location-aware Applications in Sensor Networks

Many sensor network applications require location awareness, but it is often too expensive to include a GPS receiver in a sensor network node. Hence, localization schemes for sensor networks typically use a small number of seed nodes (a.k.a. beacon or anchor) that know their location and protocols whereby other nodes estimate their location from the messages they receive. It is the task of discovering the 2D or 3D positions of the sensor nodes. Distributed computation and robustness in the presence of measurement noise are key ingredients for a practical localization algorithm that will give reliable results over a large scale network.

Service Scheduling for QoS provision in Wireless Broadband Access Networks (static or mobile)

Wireless broadband services for users is beginning to receive a lot attention lately due to ease of deployment. Some similar pre-standard services are becoming available in Australia through Unwired® and iBurst®. In this work, we will investigate the MAC protocol proposed by IEEE 802.16 committee. Accordingly, a suitable QoS architecture with suitable a scheduling scheme will be introduced to support differentiated services in a one-to-many scenario.

Design of Energy aware Routing protocols using Swarm Intelligence for Wireless Networks

The seemingly chaotic foraging behaviour of individual natural agents such an ant or a bee, are observed to result in optimal benefit for its community (swarm). By just using simple rules within each agent or at the processing nodes, a swarm of agents could induce improved performance or robustness of the system. In this work, we would look at the application of these swarm intelligence to mainly improve the network routing performance from the energy usage standpoint either in wireless sensor networks, wireless ad hoc networks or wireless mesh networks.

Self-Configurable Network Architecture for Wireless Mesh Networking

Multihop ad hoc networks are emerging as a flexible and low-cost extension to the wired infrastructure networks to serve as broadband backhaul networks. Such networks could be readily realised using off-the-shelf solutions using WiFi or WiMax products. Some useful applications for WMNs are intelligent transportation, public safety, public Internet access and community applications. Unfortunately, the network protocols of the current standards (802.11, 802.16 and 802.15) are not optimised for the peer-to-peer multihop architecture. There is a scalability limit as the network diameter increases. There are research challenges in the design of new scalable scheduling algorithm, MAC and routing protocols to efficiently manage the data traffic. The design with a cross-layer view may also be beneficial. As a special case of ad hoc networking, mesh networking should involve self-management, self-configuration and self-healing features in all layers of the network architecture.

Channel Assignment for Multi-Channel Wireless Mesh Networks

A single-channel wireless LAN might be suitable for a small group of mobile ad hoc nodes to use and share. As the number of nodes increases, a single collision domain network becomes a severe bottleneck due to increased collisions and interference. Also, there are efforts to extend traditional hotspots over multihop to provide wider service coverage at a lower deployment cost. Using multi-NICs APs operating in non-overlapping channels might be the way forward. In this project, you will investigate suitable channel assignment algorithms to improve network throughput.

QoS routing for Wireless Mesh Networks

QoS provisioning is a critical issue in designing future WMNs to support multimedia applications. These applications are typically delay-sensitive and require certain guarantees. Providing such guarantees is challenging as the medium is shared, network topology is dynamic and interference due to intra- and inter-path traffic. In this project, you will design and investigate the QoS extensions to traditional single path ad hoc routing protocols such as AODV, or adopt a multi-path routing approach.

Uncovering ancient coevolutionary events

Three quarters of emergent diseases come to humans from other species. These include, and are by no means limited to, SARS, HIV, Ebola and 'Flu. Despite the clear health issues very little is known about the general dynamics of these "zoonosis" events.
While it is well understood that the evolution of some biological species is closely linked with others, for example in parasites and their hosts or pathogens and their victims such as the emergent disease above, it is not known how well we can hope to recover the events that occurred in their shared evolutionary history, that gave rise to the patterns of associations that we can observe today. These events include simultaneous speciation (cospeciation) of host and parasite species, independent speciation of either host or parasite, and parasites "switching" hosts to infect different host species. Methods of recovering what really took place are hampered by "untraceable" events, where for instance host species went extinct or parasites 'tried' to switch hosts and failed.

This project will extend simulation software (written in C++ in a command-line environment) to output simulated histories according to a simple coevolutionary model under different model parameters. The program will output data in a format for cophylogenetic analyses with other existing software. The project will then determine which events are recovered by a range of possible approaches in the literature, and will result in a better understanding of how we can recover ancient coevolutionary dynamics from molecular sequence data.

Model Covering and Phylogenetic Reconstruction

A central problem in recovering evolutionary trees (phylogenies) from molecular (DNA) sequence data is that of which evolutionary model to use. While it is generally held that multiple processes are involved in the evolution of a single set of related molecular sequences, most phylogenetic methods either apply a single general model of sequence evolution, or partition the data very crudely into 1st, 2nd and 3rd codon positions (3rd position is highly redundant as often two or four DNA codons differing only in the 3rd position code for the same amino acid). This is a gross simplification of the underlying processes and cannot help us fully understand the complex processes underlying molecular evolution. Another result of this simplification is that phylogenetic reconstruction methods do not stand the best chance of accurately recovering the true history of the organisms involved. One successful method to date clusters the sequences into groups that do not differ by a certain amount, in order to maximise the chance of constructing each subtree accurately, before combining them with existing software.

This project will develop a data partitioning program in C++ to run in a command-line environment. The program will use greedy heuristics to assign subsets of the data into different overlapping subsets to maximise the probability of constructing the complete tree from the reconstructed subtrees. Real molecular data will be obtained from the public databases, and different data partitioning methods will be compared to find the best ones.

Deadline-Driven Packet Delivery for Wireless Sensor Networks

Wireless sensor networks have found it way into many mission-critical real-time applications such as target tracking, security surveillance and planet exploration. In these applications, timely delivery of sensory data is critical for their success in the associated response generation through suitable actuators. This implies that appropriate traffic control functions like scheduling, queuing, packet discard and/or congestion control are needed to achieve certain level of quality of service. In this project, we will design and test suitable schemes using an open-source simulator (like J-Sim). Then, the scheme will be implemented on Sun Microsystems SunSpot® sensor nodes for real-world experimentation.
Contact: Dr. S. Selvakennedy

Design of a Practical Location Scheme to Support Geographic Routing in Wireless Sensor Networks

There are numerous wireless sensor network applications that require the location service to be able to provide useful information about the monitored terrain. For instance, a network monitoring bush-fires needs to report critical events along with their locations to be any use for the emergency service. Even though GPS receivers are available now to provide quite accurate location information, they are economical prohibitive to be installed on a large scale. In this project, we will design and simulate a range-free location service for sensor networks. It will then be used to support a well-known geographic routing protocol. Once thoroughly tested, the schemes will be implemented on the Sun Microsystems SunSpot® sensors for real-world experimentation.
Contact: Dr. S. Selvakennedy

Design of a Light-Weight Middleware for Event Processing in Wireless Sensor and Actuator Network

While monitoring a terrain, critical events may occasionally be detected. Such situations may require real-time processing and respond generation without any user interruption. To generate such a response, we need to gather detail event properties such as event area, event edge and epicentre. Many such events require collaborative processing among affected nodes, and a coordinated control of the actuators. In this project, we will design a suitable middleware to support in-network event processing and response generation. The middleware will be simulated and exercised against different event properties. Later, it will be implemented on Sun Microsystems SunSpot® sensors for real-world experimentation.
Contact: Dr. S. Selvakennedy

Lightweight Time Synchronisation for Wireless Sensor Networks

Time synchronisation is a crucial issue for the correct operation of deployed sensor networks in terms of accurate time stamping of events and fine-tuned coordination of nodes’ wake/sleep duty cycles. More importantly, if the sleep times are unsynchronised, packets of critical events may be delayed or even lost in the network. Any proposed time synchronisation protocol for WSNs needs to be accurate and lightweight. In this project, we will propose a push-based protocol to synchronise a multihop WSN against a single reference node.
Contact: Dr. S. Selvakennedy