Fig 1
Overlay network architecture. If the overlay node A has traffic for node D, it can either route it directly using the tunnel from A to D or relay it through other overlay node B or C.
Source publication
We address the problem of optimal routing in overlay networks. An overlay network is constructed by adding new overlay nodes on top of a legacy network. The overlay nodes are capable of implementing any dynamic routing policy, however, the legacy underlay has a fixed, single path routing scheme and uses a simple work-conserving forwarding policy. M...
Contexts in source publication
Context 1
... overlay architecture for a gradual move towards optimal routing was proposed in [6]. This architecture integrates overlay nodes capable of dynamic routing into an underlay network of legacy devices (see Figure 1 for an example). In this paper, we develop a throughput optimal dynamic routing algorithm for such overlay networks. ...
Context 2
... the simple network shown in Figure 4. There is one commodity, k = 1, with source node 1 and destination node 4, and a single tunnel l = (1, 2, 3, 4). Suppose that at a certain iteration, ...
Context 3
... underlay uses the shortest path routing hence creating a large number of available tunnels. Node 1 can send packets to node 3 directly via node 7 or 10 using the tunnels (1,7,5,6,3) and (1,10,7,5,6,3) respectively. However, these tunnels overlap, hence there is no benefit in using both of them. ...
Context 4
... observe our rate controller at work, we consider the network from Section VII-C with a minor modification as shown in Figure 10. We add a new overlay node 15 and a new commodity (15,14) to the network. ...
Context 5
... the third commodity interferes with both commodities 1 and 2, hence the throughput of [1.5, 1.8, 1] is not achievable. From the plot in Figure 11 we can see that the throughput vector converges to [1, 1.3, 0.5] which maximizes the total utility. We can see that this throughput vector has a smaller sum than the sum of the maximum throughput supported in Section VII-C. ...
Similar publications
Due to the growing interest for multimedia contents by mobile users, designing bandwidth and delay-e�cient distributed algorithms for data searching over wireless (possibly, mobile) \ad hoc Peer-to-Peer (P2P) content Delivery Networks (CDNs) is a topic of current interest. This is mainly due to the limited computing-plus-communication resources fea...
In P2P overlay networks, bandwidth heterogeneity affects on the quality of video streaming, since each peer has its own access rate to Internet. This problem appears clearly when the video route through the overlay paths toward the receiver, it would account a bottleneck because of peers that are in the middle of the route. To address this key chal...
Citations
... Other related works in this field have only focused on the content distribution, i.e., routing problem. For instance, Rai et al. [48] described a network in which the underlying paths are predetermined and unknown to the overlay network. Then they presented an optimal dynamic routing algorithm based on the congestion of the links in the underlying network with predetermined destinations. ...
Background:
Growing demand for medical services has increased patient waiting time due to the limited number or unbalanced distribution of healthcare centers. Healthcare teleconsultation networks are one of the potentially powerful systems to overcome this problem. Medical pathology can hugely benefit from teleconsultation networks because having second opinions is precious for many cases; however, resource planning (i.e., assignment and distribution of pathology consultation requests) is challenging due to bulky medical images of patients. This results in high setup and operational costs. The aim of this study is to design an optimal teleconsultation network for pathology labs under the supervision of medical sciences universities in Tehran, Iran.
Methods:
To avoid the setup cost, we first propose a modified hybrid peer-to-peer (P2P) overlay architecture for our telepathology network, using Iran's National Healthcare Information Network (SHAMS) as the underlying infrastructure. Then we apply optimization techniques to solve the request assignment and distribution problems in the network. Finally, we present a novel mathematical model with the objective of minimizing the variable operational costs of the system.
Results:
The efficiency of the proposed method was evaluated by a set of practical-sized network instances simulated based on the characteristics of SHAMS. The results show that the presented model and architecture can obtain optimal solutions for network instances up to 350 nodes, which covers our target network.
Conclusions:
We believe that the proposed method can be beneficial for designing large-scale medical teleconsultation networks by adjusting the constraints according to the rules and conditions of each country. Our findings showed that teleconsultation networks in countries with strong information technology (IT) infrastructures are under the influence of consultation fees, while in countries with weak IT infrastructure, the transmission costs are more critical. To the best of our knowledge, no research has so far addressed resource planning in medical teleconsultation networks using optimization techniques. Besides, the target network, i.e., pathology labs under the supervision of medical sciences universities in Tehran and the SHAMS network, are discussed for the first time in this work.
... To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior speci c permission and/or a fee. Request An overlay-underlay network consists of overlay nodes and underlay nodes [9,20,22]. e overlay nodes can implement stateof-the-art algorithms while the underlay nodes are uncontrollable and could take arbitrary (possibly adversarial) actions. Figure 1 shows an overlay-underlay network where the communications among overlay nodes rely on the uncontrollable underlay nodes. ...
... An optimal backpressure-type routing algorithm for a special case, where the underlay paths do not overlap with each other, was given in [20]. Recently, [22] showed that the overlay routing algorithms proposed in [9] [20] are not throughput-optimal in general, and developed the Optimal Overlay Routing Policy (OORP) for overlay nodes. However, all of the existing overlay routing algorithms [9,20,22] impose very stringent assumptions about the behavior of underlay nodes. ...
... Recently, [22] showed that the overlay routing algorithms proposed in [9] [20] are not throughput-optimal in general, and developed the Optimal Overlay Routing Policy (OORP) for overlay nodes. However, all of the existing overlay routing algorithms [9,20,22] impose very stringent assumptions about the behavior of underlay nodes. In particular, the underlay nodes are required to use xed-path routing (e.g., shortest-path routing) and maintain stability whenever possible, which fails to account for many important underlay policies (e.g., underlay nodes may use multi-path routing). ...
The effectiveness of many well-known network control algorithms (e.g., MaxWeight) relies on the premise that all of the nodes are fully controllable. However, these algorithms may yield poor performance in a partially-controllable network where a subset of nodes are uncontrollable and may take arbitrary (possibly adversarial) actions. Such a partially-controllable model is of increasing importance in real-world networked systems such as overlay-underlay networks and uncooperative wireless networks. In this paper, we study two fundamental network optimization problems in a network with adversarial uncontrollable nodes. First, we investigate the network stability problem where the objective is to stabilize the network whenever possible. We develop a lower bound on the total queue length that can be achieved by any causal policy, and propose a throughput-optimal algorithm, called Tracking-MaxWeight (TMW), which enhances the original MaxWeight algorithm with an explicit learning of the behavior of uncontrollable nodes. Second, we study the network utility maximization problem where the objective is to maximize cumulative utility subject to stability constraints. We provide a lower bound on the utility-delay tradeoff, and develop the Tracking Drift-plus-Penalty (TDP) algorithm that achieves tunable utility-delay tradeoffs.
... An optimal backpressure-type routing algorithm for a special case, where the underlay paths do not overlap with each other, was given in [16]. Recently, [19] showed that the overlay routing algorithms proposed in [3] [16] are not throughput-optimal in general, and developed the Optimal Overlay Routing Policy (OORP) for overlay nodes. However, all of the existing overlay routing algorithms [3], [16], [19] impose very stringent assumptions about the behavior of underlay nodes. ...
... Recently, [19] showed that the overlay routing algorithms proposed in [3] [16] are not throughput-optimal in general, and developed the Optimal Overlay Routing Policy (OORP) for overlay nodes. However, all of the existing overlay routing algorithms [3], [16], [19] impose very stringent assumptions about the behavior of underlay nodes. In particular, the underlay nodes are required to use fixed-path routing (e.g., shortest-path routing) and maintain stability whenever possible, which fails to account for many important underlay policies (e.g., underlay nodes may use multi-path routing). ...
... In this paper, we investigate optimal network control for a partially-controllable network. Whereas existing works (e.g., [3], [16], [19]) imposed very stringent assumptions about the behavior of uncontrollable nodes for analytical tractability, this is the first work that establishes stability results under the generalized partially-controllable network model. In particular, we develop two network control algorithms. ...
The effectiveness of many optimal network control algorithms (e.g., BackPressure) relies on the premise that all of the nodes are fully controllable. However, these algorithms may yield poor performance in a partially-controllable network where a subset of nodes are uncontrollable and use some unknown policy. Such a partially-controllable model is of increasing importance in real-world networked systems such as overlay-underlay networks. In this paper, we design optimal network control algorithms that can stabilize a partially-controllable network. We first study the scenario where uncontrollable nodes use a queue-agnostic policy, and propose a low-complexity throughput-optimal algorithm, called Tracking-MaxWeight (TMW), which enhances the original MaxWeight algorithm with an explicit learning of the policy used by uncontrollable nodes. Next, we investigate the scenario where uncontrollable nodes use a queue-dependent policy and the problem is formulated as an MDP with unknown queueing dynamics. We propose a new reinforcement learning algorithm, called Truncated Upper Confidence Reinforcement Learning (TUCRL), and prove that TUCRL achieves tunable three-way tradeoffs between throughput, delay and convergence rate.
... The first works to demonstrate the potential of overlay networks for route optimization were Detour [48] and RON (resilient overlay network) [20], inspiring many other approaches [49][50][51][52][53]. All these routing overlay technologies use the all-pair probing approach, that is, they regularly monitor the health of all overlay links in order to dynamically select the best source-destination paths in the overlay according to application-specific metrics. ...
Continuous monitoring of network resources enables to make more-informed resource allocation decisions but incurs overheads. We investigate the trade-off between monitoring costs and benefits of accurate state information for a routing problem. In our approach link delays are modeled by Markov chains or hidden Markov models. The current delay information on a link can be obtained by actively monitoring this link at a fixed cost. At each time slot, the decision maker chooses to monitor a subset of links with the objective of minimizing a linear combination of long-run average delay and monitoring costs. This decision problem is modeled as a Markov decision process whose solution is computed numerically. In addition, in simple settings we prove that immediate monitoring cost and delay minimization leads to a threshold policy on a filter which sums up information from past measurements. The lightweight method as well as the optimal policy are tested on several use-cases. We demonstrate on an overlay of 30 nodes of RIPE Atlas that we obtain delay values close to the performance of the always best path with an extremely low monitoring effort when delays between nodes are modeled with hierarchical Dirichlet process hidden Markov models.
Classic network optimization theory focuses on network models with stochastic dynamics and all nodes being observable and controllable. However, modern network systems often offer limited access and suffer from adversarial attacks. In this paper, we focus on networks with unobservable malicious nodes, where the network dynamics, such as external arrivals and control actions of malicious nodes can be adversarial. We first extend the existing adversarial network models by introducing a new maliciousness metric that constrains the dynamics of the adversary, and characterize the stability region of a network under adversarial dynamics. We then propose an algorithm that only operates on the accessible nodes and does not require direct observations of the malicious nodes, and show that our algorithm is stabilizing as long as the network dynamics are within the stability region. Finally, we show that our algorithm stabilizes the network even if the estimates of the network state are erroneous, and characterize the necessary and sufficient conditions for networks with unobservable malicious nodes to be stabilizable when subjected to estimation errors.
