We present a deep, fully convolutional neural network that learns to route a circuit layout net with appropriate choice of met al tracks and wire class combinations. Inputs to the network are the encoded layouts containing spatial location of pins to be routed. After 15 fully convolutional stages followed by a score comparator, the network outputs 8 layout layers (corresponding to 4 route layers, 3 via layers and an identity-mapped pin layer) which are then decoded to obtain the routed layouts. We formulate this as a binary segmentation problem on a per-pixel per-layer basis, where the network is trained to correctly classify pixels in each layout layer to be 'on' or 'off'. To demonstrate learnability of layout design rules, we train the network on a dataset of 50,000 train and 10,000 validation samples that we generate based on certain pre-defined layout constraints. Precision, recall and @math score metrics are used to track the training progress. Our network achieves @math on the train set and @math on the validation set. We use PyTorch for implementing our model. Code is made publicly available at this https URL .
The task of producing routes using orthogonal layers of parallel channels and vias at intersections is often tackled heuristically, since an optimal solution does not exist for this NP-complete problem @cite_11 @cite_0 @cite_18 @cite_5 . Previous work in this field @cite_22 @cite_16 @cite_6 @cite_19 @cite_27 @cite_24 mostly rely on explicit rule-based algorithms to tackle parts of this complex task. For instance, Zajc al @cite_24 proposed using hierarchical algorithms for automatic routing of interconnects in two layer channels. Rivest al @cite_16 show a "greedy" heuristic channel router assuming all pins and wiring sit on a common grid. The other class of routers, which have received attention lately, are objective function based. Alpert al @cite_20 proposed a combination of minimum spanning tree (Prim) and shortest path tree (Dijkstra) objectives for performance driven global routing. Constructing routing tree with different objectives was also explored, such as timing objective @cite_14 , buffer insertion @cite_17 and wire sizing objective @cite_4 , congestion and thermal objective @cite_2 @cite_1 . A completely different objective for diagonal routing as opposed to the orthogonal (Manhattan) routing was also proposed @cite_9 .
@cite_18 @cite_14 @cite_4 @cite_22 @cite_9 @cite_1 @cite_17 @cite_6 @cite_0 @cite_19 @cite_27 @cite_24 @cite_2 @cite_5 @cite_16 @cite_20 @cite_11
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The throughput of wireless networks can be significantly improved by multi-channel communications compared with single-channel communications since the use of multiple channels can reduce interference influence. In this paper, we study interference-aware topology control and QoS routing in IEEE 802.11-based multi-channel wireless mesh networks with dynamic traffic. Channel assignment and routing are two basic issues in such networks. Different channel assignments can lead to different network topologies. We present a novel definition of co-channel interference. Based on this concept, we formally define and present an effective heuristic for the minimum INterference Survivable Topology Control (INSTC) problem which seeks a channel assignment for the given network such that the induced network topology is interference-minimum among all K-connected topologies. We then formulate the Bandwidth-Aware Routing (BAR) problem for a given network topology, which seeks routes for QoS connection requests with bandwidth requirements. We present a polynomial time optimal algorithm to solve the BAR problem under the assumption that traffic demands are splittable. For the non-splittable case, we present a maximum bottleneck capacity path routing heuristic. Simulation results show that compared with the simple common channel assignment and shortest path routing approach, our scheme improves the system performance by 57 on average in terms of connection blocking ratio. 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. Motivated by analysis of distributed RC delay in routing trees, a new tree construction is proposed for performance-driven global routing which directly trades off between Prim's minimum spanning tree algorithm and Dijkstra's shortest path tree algorithm. This direct combination of two objective functions and their corresponding optimal algorithms contrasts with the more indirect 'shallow-light' methods. The authors' method achieves routing trees which satisfy a given routing tree radius bound while using less wire than previous methods. Detailed simulations show that these wirelength savings translate into significantly improved delay over standard MST routing in both IC and multichip module (MCM) interconnect technologies. > This paper studies a multi-facility network synthesis problem, called the Two-level Network Design (TLND) problem, that arises in the topological design of hierarchical communication, transportation, and electric power distribution networks. We are given an undirected network containing two types of nodes---primary and secondary---and fixed costs for installing either a primary or a secondary facility on each edge. Primary nodes require higher grade interconnections than secondary nodes, using the more expensive primary facilities. The TLND problem seeks a minimum cost connected design that spans all the nodes, and connects primary nodes via edges containing primary facilities; the design can use either primary or secondary edges to connect the secondary nodes. The TLND problem generalizes the well-known Steiner network problem and the hierarchical network design problem. In this paper, we study the relationship between alternative model formulations for this problem (e.g., directed and undirected models), and analyze the worst-case performance for a composite TLND heuristic based upon solving embedded subproblems (e.g., minimum spanning tree and either Steiner tree or shortest path subproblems). When the ratio of primary to secondary costs is the same for all edges and when we solve the embedded subproblems optimally, the worst-case performance ratio of the composite TLND heuristic is 4 3. This result applies to the hierarchical network design problem with constant primary-to-secondary cost ratio since its subproblems are shortest path and minimum spanning tree problems. For more general situations, we express the TLND heuristic worst-case ratio in terms of the performance of any heuristic used to solve the embedded Steiner tree subproblem. A companion paper develops and tests a dual ascent procedure that generates tight upper and lower bounds on the optimal value of a multi-level extension of this problem. During recent days, the large problem space of very large scale integrated (VLSI) circuits has led global routing problem to a NP Complete one. With the advent of three dimensional integrated circuits (3D IC) the problem has become more complex. In this paper, a multi-objective global routing technique is formulated using fuzzy logic to get rid of the limitations of deterministic approaches. During global routing the decision is taken from a fuzzy logic expert system depending upon some generated pre-routing guiding information. Proposed approach is mainly focused on the modern generation 3D ICs. This primary work is mainly incorporated in the standard cell design for 3D ICs. A two-pin global router tool is designed based on the proposed algorithm resulting 85-97 routability in negligible time for ISPD'98 benchmarks. In deep sub-micron regime, interconnect delays dominate VLSI circuit design. Thus, construction of cost-effective global routing trees is key to such designs. In order to reduce the interconnect delay, traditional Manhattan (M-) routing architectures are currently being replaced by the diagonal X architectures. A recent routing architecture is based on Y interconnects, involving the pervasive use of 0 spl deg , 60 spl deg , and 120 spl deg oriented global and semi-global wirings. Unlike the X-routing, Y-routing Is observed to support regular routing grid, which as important for simplifying manufacturing processes and routing and design rule checking algorithms. In this paper, we propose a novel Y-routing algorithm which can solve reasonably sized problems in nominal time. The proposed method is capable of finding routing solutions for problem instances which could not be solved in reasonable time by some recently reported methods. Moreover, it can be easily extended for routing with any uniform orientation. Existing position-based unicast routing algorithms which forward packets in the geographic direction of the destination require that the forwarding node knows the positions of all neighbors in its transmission range. This information on direct neighbors is gained by observing beacon messages each node sends out periodically. Due to mobility, the information that a node receives about its neighbors becomes outdated, leading either to a significant decrease in the packet delivery rate or to a steep increase in load on the wireless channel as node mobility increases. In this paper, we propose a mechanism to perform position-based unicast forwarding without the help of beacons. In our contention-based forwarding scheme (CBF) the next hop is selected through a distributed contention process based on the actual positions of all current neighbors. For the contention process, CBF makes use of biased timers. To avoid packet duplication, the first node that is selected suppresses the selection of further nodes. We propose three suppression strategies which vary with respect to forwarding efficiency and suppression characteristics. We analyze the behavior of CBF with all three suppression strategies and compare it to an existing greedy position-based routing approach by means of simulation with ns-2. Our results show that CBF significantly reduces the load on the wireless channel required to achieve a specific delivery rate compared to the load a beacon-based greedy forwarding strategy generates. The channel routing problem is a special care of the wire routing problem when interconnections have to be performed within a rectangular strip having no obstructions, between terminals located on opposite sides of the rectangle. We present here a new channel routing algorithm, based on reduction of the problem to the case of a (2 x n) grid and on consistent utilization of a "divide and conquer" approach. For the current implementation of the algorithm, the running time is proportional to N x n x log (m), where N is the number of nets, n is the length of the channel (number of columns) and m is the width of the channel (number of tracks). Traditional technological restrictions are assumed, i.e. net terminals are located on vertical grid lines, two wiring layers are available for interconnections - one layer is used exclusively for vertical segments, another for horizontal and vias are introduced for each layer change. This algorithm consistently outperforms several known routers in quality of wiring. We tested the algorithm on several benchmark problems. One of them - Deutsch's "difficult example" - was routed with only 19 horizontal wiring tracks (the absolute minimum for this case), whereas all other known routers required 20 or more tracks. We propose a routing strategy to improve the transportation efficiency on complex networks. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called efficient path, which considers the possible congestion in the nodes along actual paths. Since the nodes with the largest degree are very susceptible to traffic congestion, an effective way to improve traffic and control congestion, as our strategy, can be redistributing traffic load in central nodes to other noncentral nodes. Simulation results indicate that the network capability in processing traffic is improved more than 10 times by optimizing the efficient path, which is in good agreement with the analysis. DOI: 10.1103 PhysRevE.73.046108 PACS numbers: 89.75.Hc Since the seminal work on scale-free networks by Barabasi and Albert BA model1 and on the small-world phenomenon by Watts and Strogatz 2, the structure and dynamics of complex networks have recently attracted a tremendous amount of interest and attention from the physics community see the review papers 3‐5 and references therein. The increasing importance of large communication networks such as the Internet 6, upon which our society survives, calls for the need for high efficiency in handling and delivering information. In this light, to find optimal strategies for traffic routing is one of the important issues we have to address. There have been many previous studies to understand and control traffic congestion on networks, with a basic assumption that the network has a homogeneous structure 7‐11. However, many real networks display both scale-free and small-world features, and thus it is of great interest to study the effect of network topology on traffic flow and the effect of traffic on network evolution. present a formalism that can cope simultaneously with the searching and traffic dynamics in parallel transportation systems 12. This formalism can be used to optimize network structure under a local search algorithm, while to obtain the formalism one should know the global information of the whole networks. Holme and Kim provide an in-depth analysis on the vertex edge overload cascading breakdowns based on evolving networks, and suggest a method to avoid It was recently reported that all known face and combined greedy-face routing variants cannot guarantee message delivery in arbitrary undirected planar graphs. The purpose of this article is to clarify that this is not the truth in general. We show that specifically in relative neighborhood and Gabriel graphs recovery from a greedy routing failure is always possible without changing between any adjacent faces. Guaranteed delivery then follows from guaranteed recovery while traversing the very first face. In arbitrary graphs, however, a proper face selection mechanism is of importance since recovery from a greedy routing failure may require visiting a sequence of faces before greedy routing can be restarted again. A prominent approach is to visit a sequence of faces which are intersected by the line connecting the source and destination node. Whenever encountering an edge which is intersecting with this line, the critical part is to decide if face traversal has to change to the next adjacent one or not. Failures may occur from incorporating face routing procedures that force to change the traversed face at each intersection. Recently observed routing failures which were produced by the GPSR protocol in arbitrary planar graphs result from incorporating such a face routing variant. They cannot be constructed by the well known GFG algorithm which does not force changing the face anytime. Beside methods which visit the faces intersected by the source destination line, we discuss face routing variants which simply restart face routing whenever the next face has to be explored. We give the first complete and formal proofs that several proposed face routing, and combined greedyface routing schemes do guarantee delivery in specific graph classes or even any arbitrary planar graphs. We also discuss the reasons why other methods may fail to deliver a message or even end up in a loop. This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multi-rate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with time-varying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models. This paper considers the problem of finding minimum-energy cooperative routes in a wireless network with variable wireless channels. We assume that each node in the network is equipped with a single omnidirectional antenna and, motivated by the large body of physical layer research indicating its potential utility, that multiple nodes are able to coordinate their transmissions at the physical layer in order to take advantage of spatial diversity. Such coordination, however, is intrinsically intertwined with routing decisions, thus motivating the work. We first formulate the energy cost of forming a cooperative link between two nodes based on a two-stage transmission strategy assuming that only statistical knowledge about channels is available. Utilizing the link cost formulation, we show that optimal static routes in a network can be computed by running Dijkstra's algorithm over an extended network graph created by cooperative links. However, due to the variability of wireless channels, we argue that a many-to-one cooperation model in static routing is suboptimal. Hence, we develop an opportunistic routing algorithm based on many-to-many cooperation, and show that optimal routes in a network can be computed by a stochastic version of the Bellman-Ford algorithm. We use static and opportunistic optimal algorithms as baselines to develop heuristic link selection algorithms that are energy efficient while being computationally simpler than the optimal algorithms. We simulate our algorithms and show that while optimal cooperation and link selection can reduce energy consumption by almost an order of magnitude compared to non-cooperative approaches, our simple heuristics achieve similar energy savings while being computationally efficient as well. It is well known that in a network with arbitrary (convex) latency functions that are a function of edge traffic, the worst-case ratio, over all inputs, of the system delay caused due to selfish behavior versus the system delay of the optimal centralized solution may be unbounded even if the system consists of only two parallel links. This ratio is called the price of anarchy (PoA). In this paper, we investigate ways by which one can reduce the performance degradation due to selfish behavior. We investigate two primary methods (a) Stackelberg routing strategies, where a central authority, e.g., network manager, controls a fixed fraction of the flow, and can route this flow in any desired way so as to influence the flow of selfish users; and (b) network tolls, where tolls are imposed on the edges to modify the latencies of the edges, and thereby influence the induced Nash equilibrium. We obtain results demonstrating the effectiveness of both Stackelberg strategies and tolls in controlling the price of anarchy. For Stackelberg strategies, we obtain the first results for nonatomic routing in graphs more general than parallel-link graphs, and strengthen existing results for parallel-link graphs, (i) In series-parallel graphs, we show that Stackelberg routing reduces the PoA to a constant (depending on the fraction of flow controlled). (ii) For general graphs, we obtain latency-class specific bounds on the PoA with Stackelberg routing, which give a continuous trade-off between the fraction of flow controlled and the price of anarchy, (iii) In parallel-link graphs, we show that for any given class L of latency functions, Stackelberg routing reduces the PoA to at most α + (1 - α) · ρ(L), where α is the fraction of flow controlled and ρ(L) is the PoA of class L (when α = 0). For network tolls, motivated by the known strong results for nonatomic games, we consider the more general setting of atomic splittable routing games. We show that tolls inducing an optimal flow always exist, even for general asymmetric games with heterogeneous users, and can be computed efficiently by solving a convex program. Furthermore, we give a complete characterization of flows that can be induced via tolls. These are the first results on the effectiveness of tolls for atomic splittable games. In the interference scheduling problem, one is given a set of n communication requests described by source-destination pairs of nodes from a metric space. The nodes correspond to devices in a wireless network. Each pair must be assigned a power level and a color such that the pairs in each color class can communicate simultaneously at the specified power levels. The feasibility of simultaneous communication within a color class is defined in terms of the Signal to Interference plus Noise Ratio (SINR) that compares the strength of a signal at a receiver to the sum of the strengths of other signals. The objective is to minimize the number of colors as this corresponds to the time needed to schedule all requests. We introduce an instance-based measure of interference, denoted by I, that enables us to improve on previous results for the interference scheduling problem. We prove the upper and lower bounds in terms of I on the number of steps needed for scheduling a set of requests. For general power assignments, we prove a lower bound of @W(I ([email protected])) steps, where @D denotes the aspect ratio of the metric. When restricting to the two-dimensional Euclidean space (as in the previous work) the bound improves to @W(I [email protected]). Alternatively, when restricting to linear power assignments, the lower bound improves even to @W(I). The lower bounds are complemented by an efficient algorithm computing a schedule for linear power assignments using only O(Ilogn) steps. A more sophisticated algorithm computes a schedule using even only O(I+log^2n) steps. For dense instances in the two-dimensional Euclidean space, this gives a constant factor approximation for scheduling under linear power assignments, which shows that the price for using linear (and, hence, energy-efficient) power assignments is bounded by a factor of O([email protected]). In addition, we extend these results for single-hop scheduling to multi-hop scheduling and combined scheduling and routing problems, where our analysis generalizes the previous results towards general metrics and improves on the previous approximation factors. The efficiency of routing algorithms in ad-hoc networks is measured by delay, throughput, and energy. Here, we focus on routing algorithms optimizing energy consumption while providing small routing delay. For this, we exploit the sender beamforming gain in the line-of-sight path-loss model, where multiple nodes (each with a single antenna) cooperate for beamforming and the routing algorithms provide distributed self-synchronization. While direct point-to-point communication over distance d in the line-of-sight model needs transmission power Θ(d 2 ), and multi-hop power needs power Θ(d) and delay Θ(d), we can reduce the power to Θ(√d) or Θ(log d) depending on the geometry. We present three algorithms with different trade-offs. The first algorithm is designed for grid nodes in the plane and has a point-to-point delay of Θ(log d) and overall power consumption of Θ(√d). The second algorithm for the same geometry decreases the delay to Θ(1 over e log log d) with power Θ((√d) 1+e ) for e > 0. The third algorithm requires a three-dimensional grid network and achieves a delay of Θ(log d) and reduces the energy needed by all nodes to Θ(log d). Shortest paths computations constitute one of the most fundamental network problems. Nonetheless, known parallel shortest-paths algorithms are generally inefficient: they perform significantly more work (product of time and processors) than their sequential counterparts. This gap, known in the literature as the “transitive closure bottleneck,” poses a long-standing open problem. Our main result is an O mn e 0 +s m+n1+ e 0 work polylog-time randomized algorithm that computes paths within (1 + O (1 polylog n ) of shortest from s source nodes to all other nodes in weighted undirected networks with n nodes and m edges (for any fixed e 0 >0). This work bound nearly matches the O d sm sequential time. In contrast, previous polylog-time algorithms required nearly min O d n3 , O d m2 work (even when s =1), and previous near-linear work algorithms required near- O ( n ) time. We also present faster sequential algorithms that provide good approximate distances only between “distant” vertices: We obtain an O m+sn n e 0 time algorithm that computes paths of weight (1+ O (1 polylog n ) dist + O ( w max polylog n ), where dist is the corresponding distance and w max is the maximum edge weight. Our chief instrument, which is of independent interest, are efficient constructions of sparse hop sets . A ( d ,e)-hop set of a network G =( V,E ) is a set E * of new weighted edges such that mimimum-weight d -edge paths in V,E∪E* have weight within (1+e) of the respective distances in G . We construct hop sets of size O n1+ e 0 where e= O (1 polylog n ) and d = O (polylog n ). Interconnecting two rows of points across an intervening channel is an important problem in the design of LSI circuits. The most common methodology for producing such interconnections uses two orthogonal layers of parallel conductors and allows wires to "dogleg" arbitrarily. Although effective heuristic procedures are available for routing channels with this methodology, no efficient optimal algorithm has yet been discovered for the general case problem. We show that such an algorithm is unlikely to exist by establishing that this problem is NP-complete.