A Maximum-Flow-Based Complex Network Approach for Power System Vulnerability Analysis

On the connectivity preserving minimum cut problem

Maximum flow problem on dynamic generative network flows with time-varying bounds

A definitive classification is established for all conceivable and permissible duality states of two slightly different versions (Strang and Iri) of infinite dimensional max–flow min–cut dual optimization problems. The approach builds on three elements: (1) previous work of the first author on duality gaps in max–flow problems under appropriate choices of function spaces, (2) construction of a class of perturbations in infinite convex optimizations germane to max–flow, and (3) a previously published classification theory of duality states defined by combinations of (extended) extremal values of closed convex bifunction dual families and their homogeneous derivant bifunctions.

This paper presents a new strongly polynomial cut canceling algorithm for minimum cost submodular flow. The algorithm is a generalization of our similar cut canceling algorithm for ordinary min-cost flow. The algorithm scales a relaxed optimality parameter and creates a second, inner relaxation that is a kind of submodular max flow problem. The outer relaxation uses a novel technique for relaxing the submodular constraints that allows our previous proof techniques to work. The algorithm uses the min cuts from the max flow subproblem as the relaxed most positive cuts it chooses to cancel. We show that this algorithm needs to cancel only ${\mathrm O}(n^3)$ cuts per scaling phase, where n is the number of nodes. Furthermore, we show how to slightly modify this algorithm to get a strongly polynomial running time. Finally, we briefly show how to extend this algorithm to the separable convex cost case and that the same technique can be used to construct a polynomial time maximum mean cut canceling algorithm for submodular flow.

The network flows approach for matrices with given row and column sums

Geographic routing has been considered as an efficient, simple, and scalable routing protocol for wireless sensor networks since it exploits pure location information instead of global topology information to route data packets. Geographic routing requires the source nodes to be aware of the location of the sink nodes. How source nodes efficiently obtain the sink location information has been merely studied yet. In this paper, we propose a Sink Location Service via Inner Rectangular in Wireless Sensor Networks. A source node and a sink node send location queries and location announcement messages to specified direction respectively by geographic routing; thus, a sink location query path and a sink location announcement path is generated. The node located on a crossing point of these two paths informs the source node about the sink location information. Then the source node sends data to the sink node by geographic routing. The proposed scheme constructs a virtual restricted linear flooding zone inside the network to guarantee the existence of the crossing point. Simulation results show that proposed scheme is reliable and efficient than the existing protocols.

We present a new technique for determining how much information about a program's secret inputs is revealed by its public outputs. In contrast to previous techniques based on reachability from secret inputs (tainting), it achieves a more precise quantitative result by computing a maximum flow of information between the inputs and outputs. The technique uses static control-flow regions to soundly account for implicit flows via branches and pointer operations, but operates dynamically by observing one or more program executions and giving numeric flow bounds specific to them (e.g., 17 bits). The maximum flow in a network also gives a minimum cut (a set of edges that separate the secret input from the output), which can be used to efficiently check that the same policy is satisfied on future executions. We performed case studies on 5 real C, C++, and Objective C programs, 3 of which had more than 250K lines of code. The tool checked multiple security policies, including one that was violated by a previously unknown bug.

In this paper, we will extend the results about the parametric maximum flow problem to networks in which the parametrization of the arc capacities can involve both the source and the sink, as in Gallo, Grigoriadis, and Tarjan (1989), and also an additional node. We will show that the minimum cuts of the investigated networks satisfy a relaxed form of the generalized nesting property (Arai, Ueno, and Kajitani, 1993). A consequence is that the corresponding parametric maximum flow value function has at most n −1 breakpoints. All the minimum cut capacities can therefore be computed by O(1) maximum flow computations.

Conventionally, sink node is considered to have large hardware and energy resources; however, many times sink node is working in same conditions as source nodes, especially when deployed for monitoring of the snow environment. In this paper, an effort has been made to practically realize a sink node which is energy efficient and cost effective for monitoring applications. To save energy, the Main Power Module is designed to provide controlled powers to sensors and sub-modules. The paper discusses design aspects of the sink node and its long-term field evaluation with environmental sensors, especially the Snow Depth Sensor of MaxBotix. Field performance of Snow Depth Sensor has been enhanced by Euclidean Minimum Distance filter which improved the correlation of data to 0.997. The proposed design helps to achieve energy consumption of 42.72mWh which is significantly lower than the previous work. The reliable working of the sink node in the long-term field evaluation indicates that snow environment can be monitored at less expense of energy by employing proposed sensors and the specially designed sink node.

We consider the two-commodity flow problem and give a good characterization of the optimum flow if the augmented network (with both source-sink edges added) is planar. We show that max flow ≧ min cut −1, and describe the structure of those networks for which equality holds.

This paper investigates the application of a minimum loss path finding algorithm to determine the maximum flow in generalized networks that are characterized by arc losses or gains. In these generalized network flow problems, each arc has not only a defined capacity but also a loss or gain factor, which must be taken into consideration when calculating the maximum achievable flow. This extension of the traditional maximum flow problem requires a more comprehensive approach, where the maximum amount of flow is determined by accounting for additional factors such as costs, varying arc capacities, and the specific loss or gain associated with each arc. This paper extends the classic Ford–Fulkerson algorithm, adapting it to iteratively identify source-to-sink (s − t) residual directed paths with minimum cumulative loss and generalized augmenting paths (GAPs), thus enabling the efficient computation of maximum flow in such complex networks. Moreover, to enhance the computational performance of the proposed algorithm, we conducted extensive studies on parallelization techniques using graphics processing units (GPUs). Significant improvements in the algorithm’s efficiency and scalability were achieved. The results demonstrate the potential of GPU-accelerated computations in handling real-world applications where generalized network flows with arc losses and gains are prevalent, such as in telecommunications, transportation, or logistics networks.

Sensor networks to autonomously collect data and send it to the cloud via gateways are expecting for providing various IoT services. In many cases, the service providers need to build their own sensor network and many sensors to measure same data will place in a narrow area. To solve this problem, we have proposed an Information-Centric Networking based wireless Sensor Network (ICSN) to provide multiple IoT services. Also, we have proposed an ICSN Platform (ICSNP) that provides the functions of executing IoT services in sink nodes. However, the number of requests increases due to increasing number of services simultaneously at the sink node. It causes performance degradation due to rising processing load. Therefore, we have proposed the cloud-based load distribution model for application to an environment of multiple IoT services. In this paper, we evaluated the node load focusing on the sensor data acquisition interval by implementing the proposed model. As a result, the proposed method can reduce the load on the sink node compared to the conventional method even in an environment with many concurrently connected applications and short sensor data acquisition intervals. Therefore, the relationship between the acquisition interval and load in actual operation are indicated.

An agent based geographic routing protocol is proposed to improve the well-known geographic routing protocol-GPSR routing protocol. In the proposed scheme, the agent is selected by sink node which concern about the source node`s position as well as agent candidate`s state. So packets will first be forwarded to agent and next step is to be forwarded to their final goal- sink node from agent. During the next hop selection process, nodes select their neighbors by considering not only position but also their average available buffer size. This results in efficient selection of next hop node in congestion area, and then increases the successful packet delivery ratio. The simulation is conducted for two scenarios: general number of connections and large number of connections in our map. Results show that new method with agent achieves improved performance in successful packet delivery ratio when compares to GPSR without our scheme.

This paper presents a study on development of a model to analyse the concurrent multi band RF signal propagation in MANET with Space Frequency (SF) reuse. The simulation studies on the developed model clearly substantiates the realization of independent links between the source and destination nodes of MANETs with multiple hops. Drawing an analogy of repeaters in a conventional Microwave Communication Link (MCL), the model developed using AWR software simulates the basic communication operations involved in source node, multiple intermediate nodes and the destination node. Numerous simulation results are presented to illustrate the satisfactory reception of signal at the destination node of a MANET under: (a) Single path transmission with a single and Dual Frequency (DF) band of operation (b) Single path operation with combination of Omni mode and (c) Directional mode with each mode operating at a different frequency band (equal and unequal number of hops). Through satisfactory reception of signals in all the above stated scenarios, the validity of SF reuse concept as applied to a MANET system has been substantiated. This in turn implies the existence of virtually two independent RF links for concurrent data transmission. The results of MATLAB simulations reveal that SF concept delivers a throughput improvement by a factor of about 1.95 as compared to a conventional data transmission through a single path using single frequency.

An adversary can deploy parasitic sensor nodes into wireless sensor networks to collect radio traffic distributions and trace back messages to their source nodes. Then, he can locate the monitored targets around the source nodes with a high probability. In this paper, a Source-location privacy Protection scheme based on Anonymity Cloud (SPAC) is proposed. We first design a light-weight (t, n)-threshold message sharing scheme and map the original message to a set of message shares which are shorter in length and can be processed and delivered with minimal energy consumption. Based on the shares, the source node constructs an anonymity cloud with an irregular shape around itself to protect its location privacy. Specifically, an anonymity cloud is a set of active nodes with similar radio actions and they are statistically indistinguishable from each other. The size of the cloud is controlled by the preset number of hops that the shares can walk in the cloud. At the border of the cloud, the fake source nodes independently send the shares to the sink node through proper routing algorithms. At last, the original message can be recovered by the sink node once at least t shares are received. The simulation results demonstrate that the SPAC can strongly protect the source-location privacy in an efficient manner. Moreover, the message sharing mechanism of SPAC increases the confidentiality of network data and it also brings high tolerance for the failures of sensor nodes to the data transmission process.