Ali Sydney

Characterising the robustness of complex networks

With increasingly ambitious initiatives such as GENI and FIND that seek to design the future Internet, it becomes imperative to define the characteristics of robust topologies, and build future networks optimized for robustness. This paper investigates the characteristics of network topologies that maintain a high level of throughput in spite of multiple attacks. To this end, we select network topologies belonging to the main network models and some real world networks. We consider three types of attacks: removal of random nodes, high degree nodes, and high betweenness nodes. We use elasticity as our robustness measure and, through our analysis, illustrate that different topologies can have different degrees of robustness. In particular, elasticity can fall as low as 0.8% of the upper bound based on the attack employed. This result substantiates the need for optimized network topology design. Furthermore, we implement a tradeoff function that combines elasticity under the three attack strategies and considers the cost of the network. Our extensive simulations show that, for a given network density, regular and semi-regular topologies can have higher degrees of robustness than heterogeneous topologies, and that link redundancy is a sufficient but not necessary condition for robustness.

Efficient mitigation strategies for epidemics in rural regions.

Containing an epidemic at its origin is the most desirable mitigation. Epidemics have often originated in rural areas, with rural communities among the first affected. Disease dynamics in rural regions have received limited attention, and results of general studies cannot be directly applied since population densities and human mobility factors are very different in rural regions from those in cities. We create a network model of a rural community in Kansas, USA, by collecting data on the contact patterns and computing rates of contact among a sampled population. We model the impact of different mitigation strategies detecting closely connected groups of people and frequently visited locations. Within those groups and locations, we compare the effectiveness of random and targeted vaccinations using a Susceptible-Exposed-Infected-Recovered compartmental model on the contact network. Our simulations show that the targeted vaccinations of only 10% of the sampled population reduced the size of the epidemic by 34.5%. Additionally, if 10% of the population visiting one of the most popular locations is randomly vaccinated, the epidemic size is reduced by 19%. Our results suggest a new implementation of a highly effective strategy for targeted vaccinations through the use of popular locations in rural communities.

Using GENI for experimental evaluation of Software Defined Networking in smart grids

Abstract The North American Electric Reliability Corporation (NERC) envisions a smart grid that aggressively explores advance communication network solutions to facilitate real-time monitoring and dynamic control of the bulk electric power system. At the distribution level, the smart grid integrates renewable generation and energy storage mechanisms to improve the reliability of the grid. Furthermore, dynamic pricing and demand management provide customers an avenue to interact with the power system to determine the electricity usage that best satisfies their lifestyle. At the transmission level, efficient communication and a highly automated architecture provide visibility in the power system and as a result, faults are mitigated faster than they can propagate. However, such higher levels of reliability and efficiency rest on the supporting communication infrastructure. To date, utility companies are moving towards Multiprotocol Label Switching (MPLS) because it supports traffic engineering and virtual private networks (VPNs). Furthermore, it provides Quality of Service (QoS) guarantees and fail-over mechanisms in addition to meeting the requirement of non-routability as stipulated by NERC. However, these benefits come at a cost for the infrastructure that supports the full MPLS specification. With this realization and given a two week implementation and deployment window in GENI, we explore the modularity and flexibility provided by the low cost OpenFlow Software Defined Networking (SDN) solution. In particular, we use OpenFlow to provide (1) automatic fail-over mechanisms, (2) a load balancing, and (3) Quality of Service guarantees: all essential mechanisms for smart grid networks.

Simulative Comparison of Multiprotocol Label Switching and OpenFlow Network Technologies for Transmission Operations

Utility companies are integrating multiprotocol label switching (MPLS) technologies into existing backbone networks, including networks between substations and control centers. MPLS has mechanisms for efficient overlay technologies as well as mechanisms to enhance security: features essential to the functioning of the smart grid. However, with MPLS routing and other switching technologies innovation is restricted to the features enclosed “in the box.” More specifically, there is no practical way for utility operators or researchers to test new ideas such as alternatives to IP or MPLS on a realistic scale to obtain the experience and confidence necessary for real world deployments. As a result, novel ideas go untested. Conversely, the OpenFlow framework has enabled significant advancements in network research. OpenFlow provides utility operators and researchers the programmability and flexibility necessary to enable innovation in next-generation communication architectures for the smart grid. This level of flexibility allows OpenFlow to provide all features of MPLS and also allows OpenFlow devices to co-exist with existing MPLS devices. The simulation results in this paper demonstrate that OpenFlow performs as well as MPLS, and may therefore be considered an alternative to MPLS for smart grid applications.

The impact of optimizing algebraic connectivity in hierarchical communication networks for transmission operations in smart grids

Most recently, algebraic connectivity has been used in the ongoing research effort that characterizes the robustness of networks to failures and attacks: the larger the algebraic connectivity, the more robust a network, and thus, the larger the number of links that must be removed to fragment the network. In this paper, we investigate the impact on the topology and traffic characteristics of the communication network that supports the transmission component of the smart grid, as links are added/rewired to maximally increase algebraic connectivity. Conventionally, the topology of the communication network tends to be identical to that of the power network. However, we first illustrate through a Demand Response (DR) application that a topology which may be ideal for the power network, may not necessarily be ideal for the communication network. Secondly, we demonstrate how concepts from graph theory can dramatically improve the performance characteristics of a communication network. Finally, we show that in certain cases, rewiring or adding links provide the same level of performance. Thus, network engineers at the initial stage of deploying communication infrastructure, can opt for either solution depending on financial constraints.

Building Application-Aware Network Environments using SDN for Optimizing Hadoop Applications

Hadoop has become the de facto standard for Big Data analytics, especially for workloads that use the MapReduce (M/R) framework. However, the lack of network awareness of the default MapReduce resource manager in Hadoop can cause unbalanced job scheduling, network bottleneck, and eventually increase the Hadoop run time if Hadoop nodes are clustered in several geographically distributed locations. In this paper, we present an application-aware network approach using software-defined networking (SDN) for distributed Hadoop clusters. We develop the SDN applications for this environment that consider network topology discovery, traffic monitoring, and flow rerouting in addition to loop avoidance mechanisms.