Tree-based Network Research Articles

Adaptive Mechanism for Discovering Internet Gateways in Wireless Networks Using Swarm Intelligence

One of the most critical and challenging processes is the provision of internet connectivity for nodes in Wireless Mesh Networks (WMN) or mobile ad hoc networks (MANET). A wide variety of “business and non-commercial” applications are implemented in MANET, most of them gaining Internet resources. Gateway (GW) or Mesh GWs are the key components of MANET's Internet connectivity, and multiple GWs are implemented to improve MANET's capabilities. Many of the current routing protocols are implemented and improved to work with MANET, either using traditional routing approaches or tree-based network approaches. But since MANET is a complex and transient network, it is very necessary to explore new or tack the GWs failure that adds more overhead on the network. Thus, in this paper a hybrid protocol inspired by the swarm intelligence technique that follows the non-root GWs discovery approach using Ant Colony Optimization (ACO) is suggested. The experimental results validate the processes of exploring new GWs, testing and maintaining existing paths to GWs, exploring different paths to existing GWs and detecting any connection failure in any route, and attempting to fix that failure.

A Structure Theorem for Rooted Binary Phylogenetic Networks and Its Implications for Tree-Based Networks

Attempting to recognize a tree inside a phylogenetic network is a fundamental undertaking in evolutionary analysis. In the last few years, therefore, “tree-based” phylogenetic networks, which are d...

Heterogeneous Networks in 5g using Joint Path Selection and Efficient Self Organization Protocol

Tree networks are systematically spread across multiple networks. This project proposes a framework for effective self-organization for 5 G heterogeneous networks. All nodes in this network are classified into two types: network nodes, and non-network nodes. Network nodes are able to broadcast packets to neighboring nodes. A tree-based network can then be obtained from one layer to another. The topology is dynamically balanced to balance energy consumption and extend the service life of the network. To test the current technique we perform tests with it. Results from the simulation show our proposed protocol can easily create a stable tree-based network. As the network size rising, the time for self-organization, average hop and error ratio for packets does not change any more. In comparison, packet success rates in effective self-organization protocol are significantly higher compared to AODV and DSDV. Non-network nodes collect the packets being transmitted and decide whether to access the network. We use various metrics such as number of child nodes, hop, contact distance and residual energy to meet the available sink nodes weight during the self-organizing process, the node with highest weight is selected as sink node. Non-network nodes will be transformed to network nodes if they effectively join the network.

The Space of Tree-Based Phylogenetic Networks.

Phylogenetic networks are generalizations of phylogenetic trees that allow the representation of reticulation events such as horizontal gene transfer or hybridization, and can also represent uncertainty in inference. A subclass of these, tree-based phylogenetic networks, have been introduced to capture the extent to which reticulate evolution nevertheless broadly follows tree-like patterns. Several important operations that change a general phylogenetic network have been developed in recent years and are important for allowing algorithms to move around spaces of networks; a vital ingredient in finding an optimal network given some biological data. A key such operation is the nearest neighbour interchange, or NNI. While it is already known that the space of unrooted phylogenetic networks is connected under NNI, it has been unclear whether this also holds for the subspace of tree-based networks. In this paper, we show that the space of unrooted tree-based phylogenetic networks is indeed connected under the NNI operation. We do so by explicitly showing how to get from one such network to another one without losing tree-basedness along the way. Moreover, we introduce some new concepts, for instance "shoat networks", and derive some interesting aspects concerning tree-basedness. Last, we use our results to derive an upper bound on the size of the space of tree-based networks.

Classes of tree-based networks

Recently, so-called tree-based phylogenetic networks have attracted considerable attention. These networks can be constructed from a phylogenetic tree, called the base tree, by adding additional edges. The primary aim of this study is to provide sufficient criteria for tree-basedness by reducing phylogenetic networks to related graph structures. Even though it is generally known that determining whether a network is tree-based is an NP-complete problem, one of these criteria, namely edge-basedness, can be verified in linear time. Surprisingly, the class of edge-based networks is closely related to a well-known family of graphs, namely, the class of generalized series-parallel graphs, and we explore this relationship in full detail. Additionally, we introduce further classes of tree-based networks and analyze their relationships.

TBCNN 기반 코드 클론 유형 분류

TBCNN 기반 코드 클론 유형 분류

A Stepwise and Hybrid Trust Evaluation Scheme for Tactical Wireless Sensor Networks.

In tactical wireless sensor networks, tactical sensors are increasingly expected to be exploited for information collection in battlefields or dangerous areas on behalf of soldiers. The main function of these networks is to use sensors to measure radiation, nuclear, and biochemical values for the safety of allies and also to monitor and carry out reconnaissance of enemies. These tactical sensors require a network traffic flow that sends various types of measured information to the gateway, which needs high reliability. To ensure reliability, it must be able to detect malicious nodes that perform packet-dropping attacks to disrupt the network traffic flow, and energy-constrained sensors require energy-efficient methods to detect them. Therefore, in this paper, we propose a stepwise and hybrid trust evaluation scheme for locating malicious nodes that perform packet-dropping attacks in a tree-based network. Sensors send a query to the gateway by observing the traffic patterns of their child nodes. Moreover, depending on the situation, the gateway detects malicious nodes by choosing between gateway-assisted trust evaluation and gateway-independent trust evaluation. We implemented and evaluated the proposed scheme with the OPNET simulator, and the results showed that a higher packet delivery ratio can be achieved with significantly lower energy consumption.

How tree-based is my network? Proximity measures for unrooted phylogenetic networks

Tree-based networks are a class of phylogenetic networks that attempt to formally capture what is meant by “tree-like” evolution. A given non-tree-based phylogenetic network, however, might appear to be very close to being tree-based, or very far. In this paper, we formalize the notion of proximity to tree-based for unrooted phylogenetic networks, with a range of proximity measures. These measures also provide characterizations of tree-based networks. One measure in particular, related to the nearest neighbour interchange operation, allows us to define the notion of “tree-based rank”. This provides a subclassification within the tree-based networks themselves, identifying those networks that are “very” tree-based. Finally, we prove results relating tree-based networks in the settings of rooted and unrooted phylogenetic networks, showing effectively that an unrooted network is tree-based if and only if it can be made a rooted tree-based network by rooting it and orienting the edges appropriately. This leads to a clarification of the contrasting decision problems for tree-based networks, which are polynomial in the rooted case but NP complete in the unrooted.

A PROPOSED SOLUTION TO THE BOTTLENECK AND CAPACITY PROBLEM FOR DATA TRANSFER

There is increased need for solution to communicate larger data over the PON network. In this study, two problems including bottleneck and the capacity load problem were investigated and based on this, a solution is proposed. For methodology, N number of Nodes is used for ringbased architecture which represent the complete PON system. The nodes are the save points are created for monitoring the nodes and tracking their network faults. The distance from each node is equal and there are N number of checkpoints. The source and receiver node are selected dynamically. A ring-based network model is proposed with the optimized solution, less data loss and higher speed. The proposed work sets a scenario which is based on ring topology with 08 number of nodes with same number of save points. 800 m * 800 m is the dimension of the topography. We found that time it took to transfer a packet is about 1.01 second. For solving the bottleneck problem, the tree-based network model is used and accordingly, 4 sub-networks are taken in a hierarchal way. Comparison of results based on packet delivery shows that proposed model has better time factor in terms of sending data compared to the existing system.

Directed Placement for mVLSI Devices

Continuous-flow microfluidic devices based on integrated channel networks are becoming increasingly prevalent in research in the biological sciences. At present, these devices are physically laid out by hand by domain experts who understand both the underlying technology and the biological functions that will execute on fabricated devices. The lack of a design science that is specific to microfluidic technology creates a substantial barrier to entry. To address this concern, this article introduces Directed Placement, a physical design algorithm that leverages the natural “directedness” in most modern microfluidic designs: fluid enters at designated inputs, flows through a linear or tree-based network of channels and fluidic components, and exits the device at dedicated outputs. Directed placement creates physical layouts that share many principle similarities to those created by domain experts. Directed placement allows components to be placed closer to their neighbors compared to existing layout algorithms based on planar graph embedding or simulated annealing, leading to an average reduction in laid-out fluid channel length of 91% while improving area utilization by 8% on average. Directed placement is compatible with both passive and active microfluidic devices and is compatible with a variety of mainstream manufacturing technologies.

Failure prediction, detection & recovery algorithms using MCMC in tree-based network topology to improve coverage and connectivity in 3D-UW environment

In an Underwater Wireless Sensor Networks (UW-WSN), one of the most challenging issue is the fault tolerance during data transmission. There are various constraints like lack of power, physical damage, hardware and software problem that leads to failure or blocked sensor node. Due to the faulty sensor node, it is quite difficult to communicate the information in a particular time period. This failure affects the overall network operation performance. In order to improve the coverage, connectivity and network performance, we propose a failure prediction, detection and recovery algorithm using Markov Chain Monte Carlo (MCMC) process. In the failure prediction algorithm, the failures of sensor node are identified by using error pattern of delayed messages and the threshold limit is based on time probability distribution function. In the failure detection algorithm, the faulty sensor node is detected using threshold limit and residual energy. In the recovery algorithm, the faulty sensor node is replaced by the nearest neighbouring sensor node with high energy capacity. Theoretical analysis and experimental simulation results are evaluated based on performance metrics such as Coverage Ratio, Failure Prediction, Network Lifetime and Recovery Policy. The results shows that the proposed 3-D UW-WSN system has a maximum coverage ratio of 23.07%, maximum increase of recovery sensor nodes 30%, maximum decrease of the predictive probability of failure node 11.11% and maximum increase of network lifetime 50%. The simulation results shows better performance and the proposed method is more efficient than the coverage of static and mobile sensor in 2-D UW-WSN algorithms. The proposed coverage of static and mobile sensor in 3-D UW-WSN mechanism performs to improve coverage and connectivity, reduces the predictive probability of failure nodes and increases network lifetime.

On the Subnet Prune and Regraft Distance

Phylogenetic networks are rooted directed acyclic graphs that represent evolutionary relationships between species whose past includes reticulation events such as hybridisation and horizontal gene transfer. To search the space of phylogenetic networks, the popular tree rearrangement operation rooted subtree prune and regraft (rSPR) was recently generalised to phylogenetic networks. This new operation – called subnet prune and regraft (SNPR) – induces a metric on the space of all phylogenetic networks as well as on several widely-used network classes. In this paper, we investigate several problems that arise in the context of computing the SNPR-distance. For a phylogenetic tree $T$ and a phylogenetic network $N$, we show how this distance can be computed by considering the set of trees that are embedded in $N$ and then use this result to characterise the SNPR-distance between $T$ and $N$ in terms of agreement forests. Furthermore, we analyse properties of shortest SNPR-sequences between two phylogenetic networks $N$ and $N'$, and answer the question whether or not any of the classes of tree-child, reticulation-visible, or tree-based networks isometrically embeds into the class of all phylogenetic networks under SNPR.

An Efficient and Accurate Link Latency Monitoring Method for Low-Latency Software-Defined Networks

This paper proposes a novel latency monitoring method for software-defined networks (SDNs) called LLDP-looping, which uses LLDP packets injected repeatedly in the control plane to determine latency between switches. It provides accurate and continuous latency monitoring without involving any dedicated network infrastructure, while avoiding potential measurement failures that can occur in the existing method of timestamping data packets as probe packets, and overcoming the major factors that decrease the measurement accuracy in many existing methods for monitoring SDN latency. We formulate an optimization problem to enable LLDP-looping to minimize its workload on both control and data planes, and propose a novel greedy algorithm to solve this problem efficiently. Evaluations over the tree-based network topologies demonstrate that LLDP-looping can effectively minimize its overhead, and provide measurement accuracy higher than 90% against the round trip time measured by Ping over an SDN with link latency as small as 0.05 ms. The advantages of LLDP-looping can be realized with minimal modifications to SDN switches and this technique can be generalized to other networking scenarios.

Tree-based networks: characterisations, metrics, and support trees.

Phylogenetic networks generalise phylogenetic trees and allow for the accurate representation of the evolutionary history of a set of present-day species whose past includes reticulate events such as hybridisation and lateral gene transfer. One way to obtain such a network is by starting with a (rooted) phylogenetic tree T, called a base tree, and adding arcs between arcs of T. The class of phylogenetic networks that can be obtained in this way is called tree-based networks and includes the prominent classes of tree-child and reticulation-visible networks. Initially defined for binary phylogenetic networks, tree-based networks naturally extend to arbitrary phylogenetic networks. In this paper, we generalise recent tree-based characterisations and associated proximity measures for binary phylogenetic networks to arbitrary phylogenetic networks. These characterisations are in terms of matchings in bipartite graphs, path partitions, and antichains. Some of the generalisations are straightforward to establish using the original approach, while others require a very different approach. Furthermore, for an arbitrary tree-based network N, we characterise the support trees of N, that is, the tree-based embeddings of N. We use this characterisation to give an explicit formula for the number of support trees of N when N is binary. This formula is written in terms of the components of a bipartite graph.

Tree-based unrooted nonbinary phylogenetic networks

Phylogenetic networks are a generalisation of phylogenetic trees that allow for more complex evolutionary histories that include hybridisation-like processes. It is of considerable interest whether a network can be considered ‘tree-like’ or not, which leads to the introduction of tree-based networks in the rooted, binary context. Tree-based networks are those networks which can be constructed by adding additional edges into a phylogenetic tree, called the base tree. Previous extensions have considered extending to the binary, unrooted case and the nonbinary, rooted case. In this paper, we extend tree-based networks to the context of unrooted, nonbinary networks in three ways, depending on the types of additional edges that are permitted. Further, we study fully tree-based networks which are phylogenetic networks in which every embedded tree is a base tree. We also extend this concept to unrooted, nonbinary, phylogenetic networks and classify the resulting networks. Finally, we derive some results on the colourability of tree-based networks, which can be useful to determine whether a network is tree-based.

A universal tree-based network with the minimum number of reticulations

A tree-based network N on X is universal if every rooted binary phylogenetic X-tree is a base tree for N. Hayamizu and, independently, Zhang constructively showed that, for all positive integers n, there exists an universal tree-based network on n leaves. For all n, Hayamizu’s construction contains Θ(n!) reticulations, while Zhang’s construction contains Θ(n2) reticulations. A simple counting argument shows that a universal tree-based network has Ω(nlogn) reticulations. With this in mind, Hayamizu as well as Steel posed the problem of determining whether or not such networks exist with O(nlogn) reticulations. In this paper, we show that, for all n, there exists a universal tree-based network on n leaves with O(nlogn) reticulations.

Matrix: Multihop Address allocation and dynamic any-To-any Routing for 6LoWPAN

Standard routing protocols for IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) are mainly designed for data collection applications and work by establishing a tree-based network topology, enables packets to be sent upwards, from the leaves to the root, adapting to dynamics of low-power communication links. In this work, we propose Matrix, a platform-independent routing protocol that utilizes the existing tree structure of the network to enable reliable and efficient any-to-any data traffic in 6LoWPAN. Matrix uses hierarchical IPv6 address assignment to optimize routing table size while preserving bidirectional routing. Moreover, it uses a local broadcast mechanism to forward messages to the right subtree when a persistent node or link failures occur. We implemented Matrix on TinyOS and evaluated its performance both analytically and through simulations on TOSSIM. Our results showed that the proposed protocol is superior to available protocols for 6LoWPAN when it comes to any-to-any data communication, concerning reliability, message efficiency, and memory footprint.

Optimal time and channel assignment for data collection in wireless sensor networks

This paper studies the joint assignment of time slots and frequency channels in treebased wireless sensor networks (WSNs) for data collection applications. In order to approximate the optimal solut...

Tree-Based Unrooted Phylogenetic Networks

Phylogenetic networks are a generalization of phylogenetic trees that are used to represent non-tree-like evolutionary histories that arise in organisms such as plants and bacteria, or uncertainty in evolutionary histories. An unrooted phylogenetic network on a non-empty, finite set X of taxa, or network, is a connected, simple graph in which every vertex has degree 1 or 3 and whose leaf set is X. It is called a phylogenetic tree if the underlying graph is a tree. In this paper we consider properties of tree-based networks, that is, networks that can be constructed by adding edges into a phylogenetic tree. We show that although they have some properties in common with their rooted analogues which have recently drawn much attention in the literature, they have some striking differences in terms of both their structural and computational properties. We expect that our results could eventually have applications to, for example, detecting horizontal gene transfer or hybridization which are important factors in the evolution of many organisms.

New characterisations of tree-based networks and proximity measures

Phylogenetic networks are a type of directed acyclic graph that represent how a set X of present-day species are descended from a common ancestor by processes of speciation and reticulate evolution. In the absence of reticulate evolution, such networks are simply phylogenetic (evolutionary) trees. Moreover, phylogenetic networks that are not trees can sometimes be represented as phylogenetic trees with additional directed edges placed between their edges. Such networks are called tree-based, and the class of phylogenetic networks that are tree-based has recently been characterised. In this paper, we establish a number of new characterisations of tree-based networks in terms of path partitions and antichains (in the spirit of Dilworth's theorem), as well as via matchings in a bipartite graph. We also show that a temporal network is tree-based if and only if it satisfies an antichain-to-leaf condition. In the second part of the paper, we define three indices that measure the extent to which an arbitrary phylogenetic network deviates from being tree-based. We describe how these three indices can be computed efficiently using classical results concerning maximum-sized matchings in bipartite graphs.