Yung Yi

Rethinking virtual network embedding: substrate support for path splitting and migration

Network virtualization is a powerful way to run multiple architectures or experiments simultaneously on a shared infrastructure. However, making efficient use of the underlying resources requires effective techniques for virtual network embedding--mapping each virtual network to specific nodes and links in the substrate network. Since the general embedding problem is computationally intractable, past research restricted the problem space to allow efficient solutions, or focused on designing heuristic algorithms. In this paper, we advocate a different approach: rethinking the design of the substrate network to enable simpler embedding algorithms and more efficient use of resources, without restricting the problem space. In particular, we simplify virtual link embedding by: i) allowing the substrate network to split a virtual link over multiple substrate paths and ii) employing path migration to periodically re-optimize the utilization of the substrate network. We also explore node-mapping algorithms that are customized to common classes of virtual-network topologies. Our simulation experiments show that path splitting, path migration,and customized embedding algorithms enable a substrate network to satisfy a much larger mix of virtual networks

Mobile data offloading: how much can WiFi deliver?

This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 97 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during a two-and-a-halfweek period in February 2010. Our trace-driven simulation using the acquired whole-day traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100-s delays, the achievable gain is less than only 2%-3%, whereas with 1 h or longer deadlines, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in contrast to the substantial gain (20%-33%) reported by the existing work even for 100-s delayed transmission using traces taken from transit buses or war-driving. In addition, a distribution model-based simulator and a theoretical framework that enable analytical studies of the average performance of offloading are proposed. These tools are useful for network providers to obtain a rough estimate on the average performance of offloading for a given WiFi deployment condition.

Base Station Operation and User Association Mechanisms for Energy-Delay Tradeoffs in Green Cellular Networks

Energy-efficiency, one of the major design goals in wireless cellular networks, has received much attention lately, due to increased awareness of environmental and economic issues for network operators. In this paper, we develop a theoretical framework for BS energy saving that encompasses dynamic BS operation and the related problem of user association together. Specifically, we formulate a total cost minimization that allows for a flexible tradeoff between flow-level performance and energy consumption. For the user association problem, we propose an optimal energy-efficient user association policy and further present a distributed implementation with provable convergence. For the BS operation problem (i.e., BS switching on/off), which is a challenging combinatorial problem, we propose simple greedy-on and greedy-off algorithms that are inspired by the mathematical background of submodularity maximization problem. Moreover, we propose other heuristic algorithms based on the distances between BSs or the utilizations of BSs that do not impose any additional signaling overhead and thus are easy to implement in practice. Extensive simulations under various practical configurations demonstrate that the proposed user association and BS operation algorithms can significantly reduce energy consumption.

REFIM: A Practical Interference Management in Heterogeneous Wireless Access Networks

Due to the increasing demand of capacity in wireless cellular networks, the small cells such as pico and femto cells are becoming more popular to enjoy a spatial reuse gain, and thus cells with different sizes are expected to coexist in a complex manner. In such a heterogeneous environment, the role of interference management (IM) becomes of more importance, but technical challenges also increase, since the number of cell-edge users, suffering from severe interference from the neighboring cells, will naturally grow. In order to overcome low performance and/or high complexity of existing static and other dynamic IM algorithms, we propose a novel low-complex and fully distributed IM scheme, called REFIM (REFerence based Interference Management), in the downlink of heterogeneous multi-cell networks. We first formulate a general optimization problem that turns out to require intractable computation complexity for global optimality. To have a practical solution with low computational and signaling overhead, which is crucial for low-cost small-cell solutions, e.g., femto cells, in REFIM, we decompose it into per-BS (base station) problems based on the notion of reference user and reduce feedback overhead over backhauls both temporally and spatially. We evaluate REFIM through extensive simulations under various configurations, including the scenarios from a real deployment of BSs. We show that, compared to the schemes without IM, REFIM can yield more than 40% throughput improvement of cell-edge users while increasing the overall performance by 10~107%. This is equal to about 95% performance of the existing centralized IM algorithm (MC-IIWF) that is known to be near-optimal but hard to implement in practice due to prohibitive complexity. We also present that as long as interference is managed well, the spectrum sharing policy can outperform the best spectrum splitting policy where the number of subchannels is optimally divided between macro and femto cells.

Max-Contribution: On Optimal Resource Allocation in Delay Tolerant Networks

This is by far the first paper considering joint optimization of link scheduling, routing and replication for disruption-tolerant networks (DTNs). The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of optimality for DTNs, called snapshot optimality where nodes are not clairvoyant, i.e., cannot look ahead into future events, and thus decisions are made using only contemporarily available knowledge. Unfortunately, the optimal solution for snapshot optimality still requires solving an NP-hard problem of maximum weight independent set and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper presents a new efficient approximation algorithm, called Distributed Max-Contribution (DMC) that performs greedy scheduling, routing and replication based only on locally and contemporarily available information. Through a simulation study based on real GPS traces tracking over 4000 taxies for about 30 days in a large city, DMC outperforms existing heuristically engineered resource allocation algorithms for DTNs.

Stochastic network utility maximisation - a tribute to Kelly's paper published in this journal a decade ago

SUMMARY Since the seminal work by Kelly on distributed network resource allocation using the language of network utility maximisation (NUM) a decade ago, there have been extensive research efforts generalising and applying NUM to model, analyse and design various network protocols and architectures. Some of these works combine the distributed optimisation approach with stochastic network models to study NUM under network dynamics occurring at the session, packet and constraint levels. We survey these works by presenting the key questions, results and methodologies in this emerging theory of stochastic network utility maximisation, followed by discussion on related work and future research challenges. Copyright

Kargus: a highly-scalable software-based intrusion detection system

As high-speed networks are becoming commonplace, it is increasingly challenging to prevent the attack attempts at the edge of the Internet. While many high-performance intrusion detection systems (IDSes) employ dedicated network processors or special memory to meet the demanding performance requirements, it often increases the cost and limits functional flexibility. In contrast, existing software-based IDS stacks fail to achieve a high throughput despite modern hardware innovations such as multicore CPUs, manycore GPUs, and 10 Gbps network cards that support multiple hardware queues. We present Kargus, a highly-scalable software-based IDS that exploits the full potential of commodity computing hardware. First, Kargus batch processes incoming packets at network cards and achieves up to 40 Gbps input rate even for minimum-sized packets. Second, it exploits high processing parallelism by balancing the pattern matching workloads with multicore CPUs and heterogeneous GPUs, and benefits from extensive batch processing of multiple packets per each IDS function call. Third, Kargus adapts its resource usage depending on the input rate, significantly saving the power in a normal situation. Our evaluation shows that Kargus on a 12-core machine with two GPUs handles up to 33 Gbps of normal traffic and achieves 9 to 10 Gbps even when all packets contain attack signatures, a factor of 1.9 to 4.3 performance improvements over the existing state-of-the-art software IDS. We design Kargus to be compatible with the most popular software IDS, Snort.

The Economic Effects of Sharing Femtocells

Femtocells are a promising technology for handling exponentially increasing wireless data traffic. Although extensive attention has been paid to resource control mechanisms, for example, power control and load balancing in femtocell networks, their success largely depends on whether operators and users accept this technology or not. In this paper, we study the economic aspects of femtocell services for the case of monopoly market, and aim to answer questions on operators revenue, user surplus, and social welfare by considering practical service types and pricing strategies. We consider three user subscription services, that is, users can access only macro BSs (mobile-only), or deploy femto BSs in their house and open / exclusively use their femto BSs (open- / closed-femto). For pricing strategies, flat pricing and partial volume pricing are exploited. The main messages include the following: 1) open-femto service is beneficial to both users and providers; 2) in flat pricing, the impact on operator revenue of allowing or blocking the access of mobile-only users to open femto BSs is minor; and 3) compared with partial volume pricing, flat pricing is advantageous to the operator when users are sensitive to price.

Open or close: On the sharing of femtocells

The femtocell is an enabling technology to handle exponentially increasing wireless data traffic. Despite extensive attentions paid to resource control, e.g., power control and load balancing in femtocell networks, the success largely depends on whether operators and users accept this technology or not. In this paper, we study the economic aspects of femtocell services with game theoretic models between providers and/or users. We consider three services: users can access only macro BSs (mobile-only), or open/exclusively use their femto BS (open or closed-femto). The main messages include: 1) it is better off for the operator to provide just the open-femto service than a mix of closed and open-femto services; 2) two polices of allowing or blocking the access of mobile-only users to open femto BS are not significantly differentiated in the revenue.

Throughput of random access without message passing

We develop distributed scheduling schemes that are based on simple random access algorithms and that have no message passing. In spite of their simplicity, these schemes are shown to provide high throughput performance: they achieve the same performance as that of some maximal scheduling algorithms, e.g. Maximum Size scheduling algorithms.