Routing Tree Construction Research Articles

Discrete Artificial Fish Swarm Algorithm-Based One-Off Optimization Method for Multiple Co-Existing Application Layer Multicast Routing Trees

As an effective multicast application mechanism, the application layer multicast (ALM) determines the path of data transmission through a routing tree. In practical applications, multiple multicast sessions often occur simultaneously; however, few studies have considered this situation. A feasible solution is to sequentially optimize each co-existing ALM routing tree. However, this approach can lead to node congestion, and, even if the node out-degree reservation strategy is adopted, an optimal solution may not be obtained. In this study, to solve the problem of routing tree construction for multiple co-existing application layer multicast sessions, an optimization model that minimizes the overall delay and instability is constructed, and a one-off optimization method based on the discrete artificial fish swarm algorithm (DAFSA) is proposed. First, Steiner node sets corresponding to the multicast sessions are selected. Then, the routing trees for each multicast session are obtained through the improved spanning tree algorithm based on the complete graph composed of Steiner node sets. The experimental results show that the proposed method can simultaneously obtain multiple co-existing ALM routing trees with a low total delay and low instability. Even if the input is a single multicast session, it can lead to ALM routing trees with a lower delay and less instability than other algorithms, and the introduction of a penalty function can effectively avoid the problem of excessive replication and forwarding loads on some end-hosts. In addition, the proposed algorithm is insensitive to parameter changes and exhibits good stability and convergence properties for networks of different sizes.

Optimal Cluster-Based Topology and Deep LSTM-Based Prediction Method for Data Reduction in IoT

In the Wireless Sensor Network (WSN), the data prediction approach is needed to attain data effectively by diminishing node energy consumption. Hence, in this research, Water cycle Fire Fly Optimization and Deep Long Short-Term Memory (WCFO+ Deep LSTM) approach is employed for aggregation and reduction of data. The processes involved in the developed method are node simulation, cluster-based topology construction, routing tree construction, and data aggregation. Initially, IoT nodes are simulated in the network environment. The cluster-based topology construction is made using the WCFO algorithm. The WCFO is developed by the integration of the Firefly Optimization Algorithm (FOA) and Water cycle algorithm (WCA). The cluster-based topology is constructed by considering the objective function that includes the parameters, including distance, delay, link quality, and energy. After that, the routing process is performed using developed WCFO approach for constructing a routing tree and estimating the optimal path. Finally, the Deep LSTM is trained by the proposed WCFO algorithm, which is utilized for executing data reduction and data aggregation process with minimum energy consumption. The devised WCFO+ Deep LSTM approach achieved better performance in terms of prediction error, delay, energy, and Packet delivery ratio (PDR) with values 0.029, 0.001[Formula: see text]s, 0.161[Formula: see text]J and 99.054%, respectively.

QoS-Aware Software-Defined Multicast in LEO Satellite Networks

The emerging low earth orbit (LEO) broadband constellations are capable of distributing videos via advanced multicasting techniques to multiplex bandwidth in both satellite access and backbone networks, thereby reducing huge amounts of traffics. Previous work on LEO-based multicast routing relied on IP multicast, which fails to employ global information to achieve the optimal bandwidth saving. In this article, we leverage the novel software-defined multicasting paradigm on LEO constellations to empower advanced video distribution with optimized multicast trees, thereby significantly outperforming conventional multicasting techniques. In the presence of quality-of-service (QoS) constraints, we propose weighted rectilinear Steiner minimal trees (WRSTs), which balance bandwidth saving and QoS requirements. Our multicast tree algorithm adopts the Voronoi diagram and Delaunay triangulation to obtain suitable candidate Steiner points, which are exploited by subsequent iterative edge substitutions for WRST construction. We also design QoS-aware multicast management schemes to deal with frequent member updates and potential failures in LEO constellations. We carry out thorough experiments to demonstrate the effectiveness and efficiency of the proposed routing tree construction algorithm and multicasting protocols when compared with traditional algorithms.

A distributed energy-efficient opportunistic routing accompanied by timeslot allocation in wireless sensor networks

Sensed data can be forwarded only in one direction to the base station in one-dimensional queue wireless sensor networks different from mesh structure, so the network lifetime will be shortened if some continuous neighboring nodes have run out of their energy. So designing routing protocols for balancing energy consumption is a challenging problem. However, traditional and existing opportunistic routing protocols for one-dimensional queue wireless sensor network proposed so far have not yet addressed this problem to prolong the network lifetime by introducing sleep mode. In this article, we propose a distributed energy-efficient opportunistic routing algorithm accompanied by timeslot allocation by using specific network topology of one-dimensional queue wireless sensor network. In our new algorithm, clustering and routing tree construction is performed while introducing the optimal relay transmission distance achieved by using opportunistic routing principle, and at the same time, interference-free wake up time is scheduled, which may optimize energy consumption and decrease the number of various control messages as possible to prolong the network lifetime. Furthermore, this improves energy efficiency by introducing the operation mode giving up cluster head role. Simulation results show that the proposed protocol can significantly improve the network performance such as energy consumption and network connectivity, when compared with other existing protocols.

SDN에서 강화학습을 통한 효과적인 멀티캐스트 라우팅 트리 생성 방법

인공지능 기술의 발전과 함께 네트워크 분야에서 라우팅 문제에 대해 강화학습(Reinforcement Learning)을 적용하는 연구들이 속속 등장하고 있다. 하지만 기본적인 강화학습 방법은 고정적인 환경을 가정하기 때문에 시간에 따라 변화하는 가변적인 네트워크 환경에서 성능에 한계를 가진다. 본 논문에서는 이러한 한계를 극복하고 SDN에서 가변적인 네트워크 환경을 잘 반영할 수 있는 심층 강화학습 기반의 멀티캐스트 라우팅 트리생성 방법을 제안한다. 본 논문에서 제안하는 방법을 평가하기 위해 다양한 네트워크 토폴로지에서 성능을 비교하는 실험을 진행하였다. 그 결과 네트워크 토폴로지가 고정된 환경에서 학습한 강화학습 에이전트보다 제안 방법으로 학습한 강화학습 에이전트가 다양한 네트워크 토폴로지에서도 보다 최적에 가까운 멀티캐스트 라우팅 트리를 생성함을 알 수 있었다.

A Global Routing Method for Graphene Nanoribbons Based Circuits and Interconnects

With extreme miniaturization of traditional CMOS devices in deep sub-micron design levels, the delay of a circuit, as well as power dissipation and area are dominated by interconnections between logic blocks. Interconnect today is causing major problems such as delay, power dissipation, and so on. In an attempt to search for alternative materials, Graphene nanoribbons have been found to be potential for both transistors and interconnects due to its outstanding electrical and thermal properties. Graphene nanoribbons provide better options as materials used for global routing trees in VLSI circuits. However, certain special characteristics of Graphene nanoribbon prohibit direct application of existing VLSI routing tree construction methods. In this article, we address this issue and propose heuristic methods for construction of Graphene nanoribbon--based minimum hybrid cost and minimum-delay Steiner trees. We compute the delays for the trees using Elmore delay approximation. Experimental results demonstrate the effectiveness of our proposed methods, which are quite encouraging.

LSTR: Lightweight and Secure Tree-Based Routing for Wireless Sensor Networks

This paper proposes a Lightweight and Secure Tree-based Routing protocol (LSTR) for Wireless Sensor Networks. The security of data routing from sensor nodes to the Base Station (BS) is achieved based on an efficient ID-based authenticated key-agreement protocol. LSTR reduces the number of required keys to a single permanent private-key preloaded in sensor nodes. This key is used subsequently to generate authenticated pairwise keys with other nodes without further digital signatures or certificates. As a result, LSTR achieves both node’s authenticity and confidentiality during data delivery at low cost and without involving the BS. In addition, a single message must be transmitted by the nodes for both the routing-tree construction and key-establishment at the same time, and which reduces the communication overheads. The performance analysis results show that LSTR reduces the storage requirements, the communication overheads and the energy dissipation compared to similar relevant works, particularly during the key-establishment. Additionally, the robustness of our scheme is highlighted through a security analysis.

Single-Layer Delay-Driven GNR Nontree Routing Under Resource Constraint for Yield Improvement

It is known that graphene nanoribbon (GNR)-based devices and interconnects can be treated to be a better alternative in nanoscale designs. In this article, given a source pin and a set of target pins inside a GNR grid-based routing plane, based on the consideration of the bending delay on one routing path, an integer linear programming (ILP)-based algorithm can be first proposed to minimize the total wirelength of a single-layer delay-driven GNR routing tree (DGNRRT). Furthermore, given a resource constraint in a single-layer DGNRRT and the connection defective rate on one routing segment, the other ILP-based algorithm can be proposed to insert a feasible set of yield-driven redundant paths to maximize the total yield gain of the inserted redundant paths under resource constraint. Finally, a feasible set of obstacle-aware redundant paths may be sequentially inserted to improve the connecting yield of a delay-driven GNR nontree routing (DGNRNTR) result under resource constraint. Compared with Das’s algorithm in the construction of a GNR routing tree, the experimental results show that our proposed ILP-based algorithm uses reasonable CPU time to increase 2.50% of the wirelength and reduce 22.85% of the maximum delay for eight tested examples on the average. Compared with Yan’s algorithm in the construction of a DGNRRT, the experimental results show that our proposed ILP-based algorithm uses reasonable CPU time to reduce 5.17% of the wirelength under the same maximum delay for eight tested examples on the average. Under two resource constraints as 50% and 65% in a DGNRNTR result, the experimental results show that the connecting yields of the eight tested DGNRRTs can be improved as 0.3939 and 0.5296 on the average by using our proposed ILP-based algorithm, respectively. Compared with the combination of the algorithm, PathInsertion, and our proposed algorithm, obstacle-aware path insertion (OAPI), the experimental results show that our proposed ILP-based algorithm can improve the connecting yields of the eight tested DGNRRTs as 0.067 and 0.0507 on the average under two resource constraints as 50% and 65%, respectively.

Multicast improvement for LOADng in Internet of Things networks

The Lightweight On-demand Ad hoc Distance-vector Routing Protocol – Next Generation (LOADng) is an emerging routing solution for low-power wireless networks, which is receiving much attention and is being adopted in Internet of Things (IoT) networks. Although the current literature has introduced improvements to allow the protocol to fulfill the requirements of a higher set of IoT applications, the multicast support stills a deficiency of the protocol. Thus, to overcome this limitation, this study proposes a multicast improvement for LOADng. The proposal, named Multicast LOADng (M-LOADng) introduces a new route discovery process to enable the construction of a multicast routing tree and perform forwarding multicast data messages. The proposed solution also introduces mechanisms to reduce the control message overhead and increase the reliability of the route discovery process. Further, M-LOADng allows multicast data transmission in three different modes. The conducted experiments, through a real testbed, show that the proposed solution can reach a reliable and constant performance in terms of quality-of-service, energy consumption, and memory usage, even when increasing the multicast group size.

SALT: Provably Good Routing Topology by a Novel Steiner Shallow-Light Tree Algorithm

In a weighted undirected graph, a spanning/Steiner shallow-light tree (SLT) simultaneously approximates: 1) shortest distances from a root to the other vertices and 2) the minimum tree weight. The Steiner SLT has been proved to be exponentially lighter than the spanning one. In this paper, we propose a novel Steiner SLT construction method called Steiner SLT (SALT), which is efficient and has the tightest bound over all the state-of-the-art general-graph SLT algorithms. Applying SALT to Manhattan space offers a smooth tradeoff between rectilinear Steiner minimum tree and rectilinear Steiner minimum arborescence for VLSI routing. The adaption also reduces the time complexity from O(n2) to O(n log n). Besides, several effective post-processing methods, including safe refinement and shallowness-constrained edge substitution, are proposed to further improve the result. The experimental results show that SALT can achieve not only short path lengths and wirelength but also small delay, compared to both classical and recent routing tree construction methods.

An algorithm for obstacle‐avoiding clock routing tree construction with multiple TSVs on a 3D IC

Effective clock tree design is an important factor for determining chip performance. In this study, the authors present a 3D clock tree design algorithm to enhance the speed and performance of a VLSI chip. The authors propose an algorithm to determine the performance of the clock network by optimising both the clock skew and the dynamic power consumption of the 3D IC clock tree. The authors propose an algorithm for clock tree design based on the Elmore Delay method and routes all the sinks efficiently considering the obstacles with the use of an optimum number of through-silicon-vias (TSVs). The proposed method starts with a segregation technique to divide the sinks into smaller zones. Subsequently, an obstacle avoiding abstract clock tree is constructed with a minimum number of TSVs and buffers. The skew and dynamic power of the tree is calculated. Consequently, the proposed method is compared with recent existing works. The experimental results so obtained are quite encouraging.

An energy efficient multi-level route-aware clustering algorithm for wireless sensor networks: A self-organized approach

Energy maintenance is one of the crucial characteristics for wireless sensor networks. Clustering techniques in WSNs is wildly used to cope with sensor network deficiencies. Organizing nodes in such clusters and specifying a particular node in each cluster to undertake the task of intra-cluster and inter-cluster data communications leads to alleviate the number of transmissions and hence longer lifetime of the Network. Most of decentralized clustering protocols are performed without any acknowledgement of a route which data traverse to reach the base station. In this paper, a new distributed energy efficient multi-level route-aware clustering algorithm for WSNs called MLRC is proposed. To establish tree among sensor nodes, MLRC applies a route conscious manner in which nodes could gain desired information about possible routes to the destination. The proposed protocol eliminates extra generation of routing control packets by implementing cluster formation and routing tree construction, concurrently. Cluster heads are elected based on effective parameters. The algorithm could moderate energy consumption of relays close to the base station with assigning probability to adjacent cluster head and avoiding the insistence on the nearest cluster head selection. Experimental results illustrate that the protocol improves network longevity in comparison with other known protocols.

IDUC: An Improved Distributed Unequal Clustering Protocol for Wireless Sensor Networks

Due to the imbalanced energy consumption among nodes in wireless sensor networks, some nodes die prematurely, which decreases the network lifetime. To solve this problem, existing clustering protocols usually construct unequal clusters by exploiting uneven competition radius. Taking their imperfection on designing the uneven competition radius and intercluster communication into consideration, this paper proposes an improved distributed unequal clustering protocol (IDUC) for wireless sensor networks, where nodes are energy heterogeneous and scattered unevenly. The cores of IDUC are the formation of unequal cluster topology and the construction of intercluster communication routing tree. Compared with previous protocols, IDUC is suitable for various network scenarios, and it can balance the energy consumption more efficiently and extend the lifetime of networks significantly.

A cross-layer QoS-aware optimization protocol for guaranteed data streaming over wireless body area networks

In this paper, we study the problem of routing, bandwidth and flow assignment in wireless body area networks (BANs). We present an adaptive joint routing and bandwidth allocation protocol for traffic streaming in BAN. Our solution considers BAN for real-time data streaming applications, where the real-time nature of data streams is of critical importance for providing a useful and efficient sensorial feedback for the user while system lifetime should be maximized. Thus, bandwidth and energy efficiency of the communication between energy constrained sensor nodes must be carefully optimized. The proposed solution takes into account nodes' residual energy during the establishment of the routing paths and adaptively allocates bandwidth to the nodes in the network. We also formulate the joint routing tree construction and bandwidth allocation problem as Mixed Integer Linear Program that maximizes the network utility while satisfying the QoS requirements. We compare the resulting performance of our protocol with the optimal solution, and show that it closes a considerable portion of the gap from the theoretical optimal solution.

A local energy consumption prediction-based clustering protocol for wireless sensor networks.

Clustering is a fundamental and effective technique for utilizing sensor nodes' energy and extending the network lifetime for wireless sensor networks. In this paper, we propose a novel clustering protocol, LECP-CP (local energy consumption prediction-based clustering protocol), the core of which includes a novel cluster head election algorithm and an inter-cluster communication routing tree construction algorithm, both based on the predicted local energy consumption ratio of nodes. We also provide a more accurate and realistic cluster radius to minimize the energy consumption of the entire network. The global energy consumption can be optimized by the optimization of the local energy consumption, and the energy consumption among nodes can be balanced well. Simulation results validate our theoretical analysis and show that LECP-CP has high efficiency of energy utilization, good scalability and significant improvement in the network lifetime.

DECOR: Distributed construction of load balanced routing trees for many to one sensor networks

Many sensor networks suffer from the energy hole problem which is a special case of load imbalance caused by the funnelling effect of many sensor nodes transmitting their data to a single, central sink. In order to mitigate the problem, a balanced routing tree is often required and this can be constructed with either a centralised or distributed algorithm. Distributed solutions are typically less effective but are significantly cheaper than centralised solutions in terms of communication overhead and they scale better for the same reason.In this paper we propose a novel distributed algorithm for the construction of a load balanced routing tree. Our proposed solution, Degree Constrained Routing, is unique in that it aims to maximise global balance during construction rather that relying on rebalancing an arbitrary tree or only maximising local balance. The underlying principle is that if all nodes adopt the same number of children as each other while the routing tree grows, then the final tree will be globally balanced. Simulation results show that our algorithm can produce trees with improved balance which results in lifetimes increased by up to 80% compared to the next best distributed algorithm.

Directivity with Efficient Routing and Centralized Scheduling Algorithms for WiMAX Based Mesh Networks-ENG

Multiple access interference is a major limiting factor for the WiMAX based Mesh Network (WMN) performance. A backbone model equipped with directional antenna for WMN with two routing tree construction algorithms, Paralleled (Para-RTC) and Balanced-Paralleled (Bala-Para-RTC) are proposed here in conjunction with fair centralized scheduling algorithm and efficient link selection criteria in certain time slot,this is an important task to minimize the effect of secondary interferences for a WMN. The use of directivity with these routing algorithms increases concurrent transmissions by making use of spatial reuse, this will result in higher system performance in terms of schedule length and Channel Utilization Ratio CUR. The results also show, that using the Para and Bala-Para RTC algorithms, without directivity, will give CURs of 15.4% and 14.3% respectively, (i.e an improvement of 3.6% & 2.5% over the 11.8% CUR).When the standard Breadth First tree routing BFT is used), and with directivity it will give the same CUR of 18.2%, (i.e an improvement of 2.8% relative to the 15.4% CUR when the BFT is used). Keywords:WiMAX, WMN, Para-RTC, Bala-Para-RTC, CUR, Schedule Length

Interference-aware multicast and broadcast routing in wireless mesh networks using both rate and channel diversity

This paper deals with the problem of load-balanced routing in multi-radio multi-rate multi-channel wireless mesh networks. Our analysis relies on the multicast and broadcast sessions, where each session has a specific bandwidth requirement. We show that using both rate and channel diversity significantly improves the network performance. Toward this goal, we propose two cross-layer algorithms named the “Interference- and Rate-aware Multicast Tree (IRMT)” and the “Interference- and Rate-aware Broadcast Tree (IRBT)”. The proposed algorithms jointly address the problems of routing tree construction, transmission channel selection, transmission rate selection, and call admission control. As an advantage, the IRMT and the IRBT algorithms consider both inter-flow and intra-flow interference. These schemes not only improve the utilization of the network resources, but also balance the traffic load over the network. Numerical results demonstrate the efficiency of the proposed algorithms in terms of the number of transmissions, the load-balancing, and the network throughput.

Utility‐driven construction of balanced data routing trees in wireless sensor networks

ABSTRACTIn wireless sensor networks, achieving load balancing in an energy‐efficient manner to improve the network lifetime as much as possible is still a challenging problem because in such networks, the only energy resource for sensor nodes is their battery supplies. This paper proposes a game theoretical‐based solution in the form of a distributed algorithm for constructing load‐balanced routing trees in wireless sensor networks. In our algorithm, load balancing is realized by adjusting the number of children among parents as much as possible, where child adjustment is considered as a game between the parents and child nodes; parents are considered as cooperative players, and children are considered as selfish players. The gained utility by each node is determined by means of some utility functions defined per role, which themselves determine the behavior of nodes in each role. When the game is over, each node gains the maximum benefit on the basis of its utility function, and the balanced tree is constructed. The proposed method provides additional benefits when in‐network aggregation is applied. Analytical and simulation results are provided, demonstrating that our proposed algorithm outperform two recently proposed benchmarking algorithms [1, 2], in terms of time complexity and communication overhead required for constructing the load‐balanced routing trees. Copyright © 2012 John Wiley & Sons, Ltd.

A Cluster-Based Routing Tree Construction Algorithm for Wireless Sensor Networks

In the architecture of wireless sensor network, routing technology at the network layer is essential. Since the clustering routing leads in good performance on data aggregation, energy minimization and so on, it has become the focus of the study routing. In this paper, a cluster-based routing tree construction algorithm for Wireless Sensor Networks is proposed. The detail of how to select the intermediate nodes to build the routing gathering tree is also described. The experiments show that the algorithm is effective to extend the network lifetime.