Large-scale timing-driven rectilinear steiner tree construction in presence of obstacles

ZigBee is the emerging industrial standard for ad hoc networks based on IEEE 802.15.4. Due to characteristics such as low data rate, low price, and low power consumption, ZigBee is expected to be used in wireless sensor networks for remote monitoring, home control, and industrial automation. Since one of the most important goals is to reduce the installation and running cost, ZigBee stack is embedded in small and cheap micro-controller units. Since tree routing does not require any routing tables to send the packet to the destination, it can be used in ZigBee end devices that have limited resources. However, tree routing has the problem that the packets follow the tree topology to the destination even if the destination is located nearby. We propose the shortcut tree routing protocol to reduce the routing cost of ZigBee tree routing by using the neighbor table that is originally defined in the ZigBee standard. While following the ZigBee tree routing algorithm, we suggest forwarding the packet to the neighbor node if it can reduce the routing cost to the destination. Simulation results show that the shortcut tree routing algorithm saves more than 30 percent of the hop count compared with ZigBee tree routing.

In Deep sub-micron design level, interconnect plays an important role in VLSI circuit designs. Traditional interconnects are facing several challenges such as delay and power dissipation. Graphene nanoribbons (GNRs) have been found to be potential alternative for both transistors and interconnects due to its outstanding electrical and thermal properties. The construction of minimum cost global routing trees is a key challenge in deep sub-micron design. The construction of such trees for traditional interconnects based on Required Arrival Time (RAT) has been reported in literature. The construction of global routing trees for GNR routing are different than that of traditional interconnects. In this paper, we propose an algorithm for the construction of cost effective global routing trees for GNR routing based on required arrival time. We formulate the GNR routing problem considering the minimization of the area of triangular grid such that delay from source to each of the sink terminals is within the given time budget. The algorithm is tested on a random set of data and the results obtained are quite encouraging.

As devices and lines shrink into the deep submicron range, the propagation delay of signals can be effectively improved by repowering the signals using intermediate buffers placed within the routing trees. Almost no existing timing driven floorplanning and placement approaches consider the option of buffer insertion. As such, they may exclude solutions, particularly early in the design process, with smaller overall area and better routability. In this paper, we propose a new methodology in which buffered trees are used to estimate wire delay during floorplanning. Instead of treating delay as one of the objectives, as done by the majority of previous work, we formulate the problem in terms of delay bounded buffered trees (DBB-tree) and propose an efficient algorithm to construct a DBB spanning tree for use during floorplanning. Experimental results show that the algorithm is very effective. Using buffer insertion at the floorplanning stage yields significantly better solutions in terms of both chip area and total wire length.

Buffer insertion and wire sizing are critical in deep submicron VLSI design. This paper studies the problem of constructing routing trees with simultaneous buffer insertion and wire sizing in the presence of routing and buffer obstacles. No previous algorithms consider all these factors simultaneously. Previous dynamic programming based algorithm is first extended to solve the problem. However, with the size of routing graph increasing and with wire sizing taken into account, the time and space requirement increases enormously. Then a new approach is proposed to formulate the problem as a series of graph problems. The routing tree solution is obtained by finding shortest paths in a series of graphs. In the new approach, wire sizing can be handled almost without any additional time and space requirement, Moreover, the time and space requirement is only polynomial in terms of the size of routing graph. Our algorithm differs from traditional dynamic programming, and is capable of addressing the problem of inverter insertion and sink polarity. Both theoretical and experimental results show that the graph-based algorithm outperforms the DP-based algorithm by a large margin. We also propose a hierarchical approach to construct routing tree for a large number of sinks.

Routing strategy with effective and saving energy is an important problem in the research on the application of wireless sensor network into the farmland micro climate and soil moisture monitoring,it analyzed the disadvantage of the layered tree routing algorithm and ZigBee routing algorithms in energy saving, combined with ZigBee network topology,establishing an optimal node analysis model based on fuzzy decision, bringing forward a new routing algorithm which is suitable for large-scale farmland gradient environment, this new algorithm find out the quantitative relation between energy consumption and routing node selecting strategy,which can greatly decrease the route hop number by routing discovery mechanism and create an optimum goal group. Simulation results showed that compared with the layered tree and ZigBee routing algorithms,the new routing algorithms can significantly reduce the energy consumption of routing process.

In this paper, we propose new approaches for solving the useful-skew tree (UST) routing problem [17]: Clock routing subject to general skew constraints. The clock layout synthesis engine of our UST algorithms is based on the deferred-merge embedding (DME) paradigm for zero-skew tree [5; 1] and bounded-skew tree [8; 2] routings; hence, the names UST/DME and Greedy-UST/DME for our algorithms. They simultaneously perform skew scheduling and tree routing such that each local skew range is incrementally refined to a skew value that minimizes the wirelength during the bottom-up merging phase of DME. The resulting skew schedule is not only feasible, but is also best for routing in terms of wirelength. The experimental results show very encouraging improvement over the previous BST/DME algorithm on three ISCAS89 benchmarks under general skew constraints in terms of total wirelength.

Obstacle-avoiding Steiner minimal tree (OASMT) construction has become a focus problem in the physical design of modern very large-scale integration (VLSI) chips. In this article, an effective algorithm is presented to construct an OASMT based on X-architecturex for a given set of pins and obstacles. First, a kind of special particle swarm optimization (PSO) algorithm is proposed that successfully combines the classic genetic algorithm (GA), and greatly improves its own search capability. Second, a pretreatment strategy is put forward to deal with obstacles and pins, which can provide a fast information inquiry for the whole algorithm by generating a precomputed lookup table. Third, we present an efficient adjustment method, which enables particles to avoid all the obstacles by introducing some corner points of obstacles. Finally, an excellent refinement method is discussed to further enhance the quality of the final routing tree, which can improve the quality of the solution by 7.93% on average. To our best knowledge, this is the first time to specially solve the single-layer obstacle-avoiding problem in X-architecture. Experimental results show that the proposed algorithm can further shorten wirelength in the presence of obstacles. And it achieves the best solution quality in a reasonable runtime among the existing algorithms.

In this article, we propose new approaches for solving the useful-skew tree (UST) routing problem [Xi and Dai 1997]: clock routing subject to general skew constraints. The clock layout synthesis engine of our UST algorithms is based on the deferred-merge embedding (DME) paradigm for the zero-skew tree (ZST) [Edahiro 1992; Chao et al. 1992] and bounded-skew tree (BST) [Cong and Koh 1995; Huang et al. 1995; Kahng and Tsao 1997; Cong et al. 1998] routings; hence, the names UST/DME and Greedy-UST/DME for our UST algorithms. Our novel contribution is that we simultaneously perform skew scheduling and tree routing so that each local skew range is incrementally refined to a skew value that minimizes the wirelength increase during the bottom-up merging phase of DME. As a result, not only is the skew schedule feasible, but also the wirelength increase is minimized at each merging step of clock tree construction. The experimental results show very encouraging improvement over the previous BST/DME algorithm on three ISCAS89 benchmarks under general skew constraints in terms of total routing wirelength.

Very large scale integration (VLSI) global routing is typically performed on a rectangular die space amidst multiple IP cores and gates, typically treated as obstacles during net routing. In this paper, we address the global routing problem of a multi-terminal net in presence of obstacles, and name it as Obstacle-avoiding Group Steiner tree (OAGST) construction. The proposed method comprises of the following procedures. Given a number of obstacles, and pins (terminals) on a die, (1) first empty rectangular regions, called maximal empty rectangles, are constructed avoiding obstacles. (2) Next, a split - and - merge technique is adopted to regenerate L-shaped rectilinear regions over the maximal empty rectangles. Partial Rectilinear Steiner tree (RST) is constructed from each L-shaped region by routing the pin terminals inside the region. (3)The split - and - merged regions are next converted to a dual graph following neighbouring corner-stich method. Finally, a complete Obstacle-avoiding Group Steiner tree/Rectilinear Steiner tree is constructed from the dual graph by redundant edge deletion. A comparative study of our algorithm with an existing work shows improvement in many cases.

This paper addresses the partition problem under the continuous domain in swarm robotics. In this problem, a swarm of n robots, randomly deployed over a rectangular workspace, are required to form K size-balanced groups within a finite amount of time. We aim to look into the problem in the presence of horizontal line obstacles. The obstacles are scattered randomly over the bounded region, and their positions remain unaltered throughout the process. In the proposed solutions, the robots are assumed to be identical, autonomous, and do not have any direct communication among themselves. The robots are memoryless, except they retain only the information of the two parameters n and K throughout the process and their states among three possible ones. Two different partition algorithms are proposed assuming full-compass axis agreement and half-compass axis agreement among the local coordinate systems of the robots. In the first case, the proposed algorithm works for both synchronous and semi-synchronous models, whereas, in the second case, the robots are assumed to be synchronous. As a pre-processing step of the partition algorithms, an assembling algorithm for the half-compass axis agreement model has also been proposed for synchronous and semi-synchronous robots.

Timeliness in query response is the major quality metric for query processing in the real-time applications of Wireless Sensor Networks (WSNs). The structure of the query routing tree directly affects the whole query processing delay as it provides the path to forward a query to the relevant nodes and return the response to the sink. In the current literature, query routing structure is designed irrespective of the variation in query loads among the sensors. As a consequence, current schemes do not guarantee for the routing tree to provide a faster path to the sensors with higher query load. This motivates the current work to consider query load in constructing and self-reconfiguring the routing tree. In this paper, we present a query load-based spanning tree construction method that reduces the query response delay as well as energy consumption in query execution and provides query response with the best possible accuracy. Simulation results illustrate the efficacy of the proposed framework.

ACA: Automatic search strategy for radioactive source

Minimizing the quantity of transmitted data and protecting the devices from the adversary environment are the main challenges hindering the advancement of Internet of Things (IoT) network. Based on the theorem of unique prime factorization that any natural number can be expressed as the product of powers of prime numbers, we introduce a new scheme in this paper for secure and efficient gathering of the IoT data. The proposed scheme consists of three phases: Setup, Secure data gathering, and Data reconstruction. In the Setup phase, the properties of the prime numbers to create an efficient clustering and routing tree algorithm are utilized to reduce the power consumption during data transmission process. The Secure data gathering phase includes secure intra and inter communication procedures. During secure intra-communication procedure, the Compressive Sensing (CS) based method of data compression and encryption is used. Moreover, the prime number properties and the Bezier curve function are used to solve the CS problems. In the secure inter-communication procedure, the security performance of the IoT based Wireless Sensor Networks (WSNs) is improved by combining Private and Public key algorithms with the consideration of the power limitation of IoT devices. Finally, the proposed scheme introduces an adept reconstruction algorithm which is a hybrid algorithm of Bees and Genetic Algorithm to successfully restore the actual sensor data from the compressed samples, which improves the reconstruction process.

As an inexpensive, scalable internet-access network, a wireless internet-access mesh network ( WIMNET ) is composed of multiple access-points ( APs ) connected by wireless links. WIMNET can improve the dependability to link or AP failures by allocating APs redundantly in the network field. Because redundant APs may increase the operational cost and degrade the performance due to increasing radio interferences, only the necessary APs for communications between the hosts and the internet gateway should be activated in conventional situations. Previously, we proposed an active AP selection algorithm to select the minimum number of APs to be activated such that the overall throughput is maximised, assuming that every link has the same constant speed. However, our preliminary experiments for the emerging high-speed IEEE802.11n protocol that should be introduced into WIMNET, found that this speed is greatly affected by the link environment such as the distance. In this paper, we present an extension of the active AP selection algorithm to efficiently select active APs under link speed changes. Besides, we extend the routing tree algorithm used in the algorithm procedure and the WIMNET simulator for throughput evaluations. We verify the effectiveness through extensive simulations in three instances.

Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs). The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO) saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime.