60,296 research outputs found
Compact Oblivious Routing
Oblivious routing is an attractive paradigm for large distributed systems in which centralized control and frequent reconfigurations are infeasible or undesired (e.g., costly). Over the last almost 20 years, much progress has been made in devising oblivious routing schemes that guarantee close to optimal load and also algorithms for constructing such schemes efficiently have been designed. However, a common drawback of existing oblivious routing schemes is that they are not compact: they require large routing tables (of polynomial size), which does not scale.
This paper presents the first oblivious routing scheme which guarantees close to optimal load and is compact at the same time - requiring routing tables of polylogarithmic size. Our algorithm maintains the polylogarithmic competitive ratio of existing algorithms, and is hence particularly well-suited for emerging large-scale networks
On Efficient Distributed Construction of Near Optimal Routing Schemes
Given a distributed network represented by a weighted undirected graph
on vertices, and a parameter , we devise a distributed
algorithm that computes a routing scheme in
rounds, where is the hop-diameter of the network. The running time matches
the lower bound of rounds (which holds for any
scheme with polynomial stretch), up to lower order terms. The routing tables
are of size , the labels are of size , and
every packet is routed on a path suffering stretch at most . Our
construction nearly matches the state-of-the-art for routing schemes built in a
centralized sequential manner. The previous best algorithms for building
routing tables in a distributed small messages model were by \cite[STOC
2013]{LP13} and \cite[PODC 2015]{LP15}. The former has similar properties but
suffers from substantially larger routing tables of size ,
while the latter has sub-optimal running time of
An Experimental Investigation of Hyperbolic Routing with a Smart Forwarding Plane in NDN
Routing in NDN networks must scale in terms of forwarding table size and
routing protocol overhead. Hyperbolic routing (HR) presents a potential
solution to address the routing scalability problem, because it does not use
traditional forwarding tables or exchange routing updates upon changes in
network topologies. Although HR has the drawbacks of producing sub-optimal
routes or local minima for some destinations, these issues can be mitigated by
NDN's intelligent data forwarding plane. However, HR's viability still depends
on both the quality of the routes HR provides and the overhead incurred at the
forwarding plane due to HR's sub-optimal behavior. We designed a new forwarding
strategy called Adaptive Smoothed RTT-based Forwarding (ASF) to mitigate HR's
sub-optimal path selection. This paper describes our experimental investigation
into the packet delivery delay and overhead under HR as compared with
Named-Data Link State Routing (NLSR), which calculates shortest paths. We run
emulation experiments using various topologies with different failure
scenarios, probing intervals, and maximum number of next hops for a name
prefix. Our results show that HR's delay stretch has a median close to 1 and a
95th-percentile around or below 2, which does not grow with the network size.
HR's message overhead in dynamic topologies is nearly independent of the
network size, while NLSR's overhead grows polynomially at least. These results
suggest that HR offers a more scalable routing solution with little impact on
the optimality of routing paths
High-Quality Fault-Resiliency in Fat-Tree Networks (Extended Abstract)
Coupling regular topologies with optimized routing algorithms is key in
pushing the performance of interconnection networks of HPC systems. In this
paper we present Dmodc, a fast deterministic routing algorithm for Parallel
Generalized Fat-Trees (PGFTs) which minimizes congestion risk even under
massive topology degradation caused by equipment failure. It applies a
modulo-based computation of forwarding tables among switches closer to the
destination, using only knowledge of subtrees for pre-modulo division. Dmodc
allows complete rerouting of topologies with tens of thousands of nodes in less
than a second, which greatly helps centralized fabric management react to
faults with high-quality routing tables and no impact to running applications
in current and future very large-scale HPC clusters. We compare Dmodc against
routing algorithms available in the InfiniBand control software (OpenSM) first
for routing execution time to show feasibility at scale, and then for
congestion risk under degradation to demonstrate robustness. The latter
comparison is done using static analysis of routing tables under random
permutation (RP), shift permutation (SP) and all-to-all (A2A) traffic patterns.
Results for Dmodc show A2A and RP congestion risks similar under heavy
degradation as the most stable algorithms compared, and near-optimal SP
congestion risk up to 1% of random degradation
QuLa: queue and latency-aware service selection and routing in service-centric networking
Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature.
We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables
Self-stabilizing interval routing algorithm with low stretch factor
A compact routing scheme is a routing strategy which suggests routing tables that are space efficient compared to traditional all-pairs shortest path routing algorithms. An Interval Routing algorithm is a compact routing algorithm which uses a routing table at every node in which a set of destination addresses that use the same output port are grouped into intervals of consecutive addresses. Self-stabilization is a property by which a system is guaranteed to reach a legitimate state in a finite number of steps starting from any arbitrary state. A self-stabilizing Pivot Interval Routing (PIR) algorithm is proposed in this work. The PIR strategy allows routing along paths whose stretch factor is at most five, and whose average stretch factor is at most three with routing tables of size O(n3/2log 23/2n) bits in total, where n is the number of nodes in the network. Stretch factor is the maximum ratio taken over all source-destination pairs between the length of the paths computed by the routing algorithm and the distance between the source and the destination. PIR is also an Interval Routing Scheme (IRS) using at most 2n( 1+lnn)1/2 intervals per link for the weighted graphs and 3n(1+ lnn)1/2 intervals per link for the unweighted graphs. The preprocessing stage of the PIR algorithm consists of nodelabeling and arc-labeling functions. The nodelabeling function re-labels the nodes with unique integers so as to facilitate fewer number of intervals per arc. The arc-labeling is done in such a fashion that the message delivery protocol takes an optimal path if both the source and the destination are located within a particular range from each other and takes a near-optimal path if they are farther from each other
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