MLCOR Model for Suppressing the Cascade of Edge Failures in Complex Network

As a decisive parameter of network robustness and network economy, the capacity of network edges can directly affect the operation stability and the construction cost of the network. This paper proposes a multilevel load–capacity optimal relationship (MLCOR) model that can substantially improve the network economy on the premise of network safety. The model is verified in artificially created networks including free-scale networks, small-world networks, and in the real network structure of the Shanghai Metro network as well. By numerical simulation, it is revealed that under the premise of ensuring the stability of the network from the destruction caused by initial internal or external damage on edge, the MLCOR model can effectively reduce the cost of the entire network compared to the other two linear load–capacity models regardless of what extent of the destruction that the network edges suffer initially. It is also proved that there exists an optimal tunable parameter and the corresponding optimal network cost for any BA and NW network topology, which can provide the reference for setting reasonable capacities for network edges in a real network at the stage of network planning and construction, promoting security and stability of network operation.

Defining the Rules and Basic Set of Funtional Elements for Effective Modeling of Communication Networks

Communication networks are complex information systems influenced by a vast amount of factors. It is critically important to forecast the paths that data take to verify the network, check its security and plan its updates. Model allows exploring processes that take place in the network without affecting performance and availability of a real network itself. With modelling it becomes possible to investigate the results of infrastructural changes introduced to the network before actually implementing them. It is important to be able to formally convert real network description into the model definition which preserves all data that is significant for network operation and skip data which is not. Outlining the rules for such conversion and using a limited set of basic functional components provide the ground for automatic model creation for the network of different levels of complexity.Proposed approach to modelling of communication networks is based on decomposition of the overall function of every particular real network component into a set of functions that belong to some predefined basic set. Functions of the basic set include L3 routing, L2 switching, packet filtering, NAT, etc. Model of a real network component is defined as a group of functional nodes each of which implements some function from the basic set.Configuration and current state of network components that influence its operation are also decomposed into elements each of which relates to some particular functional node. Configuration of network components is modelled as a set of configuration storage elements and current state is modelled as a set of current state storage elements.Links that connect real network components and links that connect functional nodes in the model are presented as singledirection channels that implement propagation of L2 frames thus simplifying the model due to excluding physical layer (L1) from the scope.Using the proposed approach to modelling may allow to formalize conversion of a real network descrip- tion to a model thus making automated modelling possible. By using a sufficient basic set of functional nodes it is possible to model the network containing components of any complexity level.

Study on SDN with Security Issues Using Mininet

The internet is faced with many problems daily, one of them is decrement in network bandwidth because of Distributed Denial of Service (DDoS) attack on host server, which deplete host resources. Researchers has been invented many protection mechanisms such as detection, trace back, prevention, reaction, and characterization are in case of DDoS attacks, which will control the number of malicious packets received by the victim. But it does not provide efficient detection technique with high rate in real time network infrastructure. Thus, modern technologies are prepared on Mininet network simulators, which give more impact to simulate the real network. The architecture of Software Defined Networks (SDN) and OpenFlow architecture is used to demonstrate a programmable network model and centralized management of real network. In this research work, we provide design of software defined network (SDN) using mininet simulator and security issues related to the Software Defined Network.

Comparison between Louvain and Leiden Algorithm for Network Structure: A Review

In the real network, there must be a large and complex network. The solution to understand that kind of network structure is using the community detection algorithms. There are a lot of other algorithms out there to perform community detection. Each of the algorithms has its own advantages and disadvantages with different types and scale of complex network. The Louvain has been experimented that shows bad connected in community and disconnected when running the algorithm iteratively. In this paper, two algorithm based on agglomerative method (Louvain and Leiden) are introduced and reviewed. The concept and benefit are summarized in detail by comparison. Finally, the Leiden algorithm’s property is considered the latest and fastest algorithm than the Louvain algorithm. For the future, the comparison can help in choosing the best community detection algorithms even though these algorithms have different definitions of community.

Dynamical analysis of diversity in rule-based open source network intrusion detection systems

Diverse layers of defence play an important role in the design of defence-in-depth architectures. The use of Intrusion Detection Systems (IDSs) are ubiquitous in this design. But the selection of the “right” IDSs in various configurations is an important decision that the security architects need to make. Additionally, the ability of these IDSs to adapt to the evolving threat-landscape also needs to be investigated. To help with these decisions, we need rigorous quantitative analysis. In this paper, we present a diversity analysis of open-source IDSs, Snort and Suricata, to help security architects tune/deploy these IDSs. We analyse two types of diversities in these IDSs; configurational diversity and functional diversity. In the configurational diversity analysis, we investigate the diversity in the sets of rules and the Blacklisted IP Addresses (BIPAs) these IDSs use in their configurations. The functional diversity analysis investigates the differences in alerting behaviours of these IDSs when they analyse real network traffic, and how these differences evolve. The configurational diversity experiment utilises snapshots of the rules and BIPAs collected over a period of 5 months, from May to October 2017. The snapshots have been collected for three different off-the-shelf default configurations of the Snort IDS and the Emerging Threats (ET) configuration of the Suricata IDS. The functional diversity investigates the alerting behaviour of these two IDSs for a sample of the real network traffic collected in the same time window. Analysing the differences in these systems allows us to get insights into where the diversity in the behaviour of these systems comes from, how does it evolve and whether this has any effect on the alerting behaviour of these IDSs. This analysis gives insight to security architects on how they can combine and layer these systems in a defence-in-depth deployment.

TESTING THE EFFECTIVENESS OF THE STREET NETWORK OF CITIES (ON THE EXAMPLE OF PETROZAVODSK)

The transport network of cities can be represented as a complex of streets and passages, as well as elements of public transport infrastructure unconnected with the street and road network. It is reasonable to represent the real network in the form of a simplified network based on graph theory to analyze the properties of the transport network. There are various methods of network connectivity assessment, including those based on various indices. According to all indicators in the street and road network of the city of Petrozavodsk it is necessary to increase the number of units. The implementation of recommendations for changes of the street and road network of the city of Petrozavodsk will reduce traffic congestion, the number of accidents and transport expenses. It is recommended to use the proposed method to assess and improve the street and road network of cities.

Optimal Design of Water Distribution Network Using Neuro – Fuzzy Technique

Present paper is intended to develop optimal policy for Water Distribution Network using Neuro- Fuzzy Technique in an effective manner. Hydraulic simulation of the Real Network is performed in Water Gems and is used for the evaluation of the system performance measure. The real network is revised by adding certain Hydraulic parameters such as PBV’s (Pressure Break Valves) and Pumps and the results are found to be within standard limits for velocity and pressure specified by CPHEEO (Central Public Health and Environmental Engineering Organization). The networks are optimized using ANFIS (Adaptive Neuro Fuzzy Interactive System) to achieve the optimal cost and to obtain maximum reliability of the network. The pipe length and diameters are considered as fuzzy variables in the model and given as inputs to the model and pressure and velocities are outputs of the model. A comparison is made which marks the proposed network optimized using ANFIS is more reliable than the real network with slight increase in cost. Chota Govindpur – Baghbera Water Supply System is used as Case Study which is located in East Singhbhum District Jharkhand, India and the source of water is Subarnarekha river originated from Nagri village in Ranchi district of Jharkhand.