Changbin Liu

Declarative automated cloud resource orchestration

As cloud computing becomes widely deployed, one of the challenges faced involves the ability to orchestrate a highly complex set of subsystems (compute, storage, network resources) that span large geographic areas serving diverse clients. To ease this process, we present COPE (Cloud Orchestration Policy Engine), a distributed platform that allows cloud providers to perform declarative automated cloud resource orchestration. In COPE, cloud providers specify system-wide constraints and goals using COPElog, a declarative policy language geared towards specifying distributed constraint optimizations. COPE takes policy specifications and cloud system states as input and then optimizes compute, storage and network resource allocations within the cloud such that provider operational objectives and customer SLAs can be better met. We describe our proposed integration with a cloud orchestration platform, and present initial evaluation results that demonstrate the viability of COPE using production traces from a large hosting company in the US. We further discuss an orchestration scenario that involves geographically distributed data centers, and conclude with an ongoing status of our work.

Towards dynamic pricing-based collaborative optimizations for green data centers

Increased demand for cloud computing services has ushered power management schemes into the frontlines of data center research. Meanwhile, market penetration of intermittent renewable energy sources (e.g., wind and solar) is on the rise. While clean and abundant, their intermittency is troubling for utility companies, requiring power balancing reserves to be deployed at anytime to precisely match consumer demand with energy availability. However, a transformative redesign of our power grid is looming, calling for the use of dynamic energy pricing to resolve this issue by possibly shaping demand. Data centers, being significant consumers with the ability to adjust power utilization in real-time (e.g., by migrating its jobs to and from other locations), are ideal candidates to participate in dynamic pricing markets. We propose a collaborative cost optimization framework by coupling utilities with data centers via dynamic pricing. We develop models describing the information exchange framework for utilities and data centers and employ a distributed constraint optimization solver, Cologne, to negotiate a mutually optimal price. An evaluation of our system has been performed using real intermittent-energy-generation trace data. Modeling the dynamic price over this trace, we show that our technique could reduce a participating data centers costs by 75%. On the side of utilities, we further show that consumer power demand can be shaped to reveal a 17% improvement on average.

A declarative perspective on adaptive manet routing

In this paper, we present a declarative perspective on adaptable extensible MANET protocols. Our work builds upon declarative networking, a recent innovation for building extensible network architectures using declarative languages. We make the following contributions. First, we demonstrate that traditional MANET protocols, ranging from proactive, reactive, to epidemic can be expressed in a compact fashion as declarative networks, and we validate experimentally the use of declarative techniques to implement traditional MANETs emulated on a testbed cluster. Second, we show that the declarative framework enables policy-driven adaptation, in which a generic set of declarative rule-based policies are used to make runtime decisions on the choice of MANET protocols. Third, we present some initial ideas on fine-grained protocol composition and adaptation, where a typical MANET protocol can be composed and adapted from simpler components.

Declarative policy-based adaptive mobile ad hoc networking

This paper presents DAWN, a declarative platform that creates highly adaptive policy-based mobile ad hoc network (MANET) protocols. DAWN leverages declarative networking techniques to achieve extensible routing and forwarding using declarative languages. We make the following contributions. First, we demonstrate that traditional MANET protocols can be expressed in a concise fashion as declarative networks and policy-driven adaptation can be specified in the same language to dictate the dynamic selection of different protocols based on various network and traffic conditions. Second, we propose interprotocol forwarding techniques that ensure packets are able to seamlessly traverse across clusters of nodes running different protocols selected based on their respective policies. Third, we have developed a full-fledged implementation of DAWN using the RapidNet declarative networking system. We experimentally validate a variety of policy-based adaptive MANETs in various dynamic settings using a combination of ns-3 simulations and deployment on the ORBIT testbed. Our experimental results demonstrate that hybrid protocols developed using DAWN outperform traditional MANET routing protocols and are able to flexibly and dynamically adapt their routing mechanisms to achieve a good tradeoff between bandwidth utilization and route quality. We further demonstrate DAWNs capabilities to achieve interprotocol forwarding across different protocols.

Declarative policy-based adaptive MANET routing

This paper presents the design and implementation of declarative policy-based adaptive MANET routing protocols. Our work builds upon declarative networking, a recent innovation for building extensible network architectures using declarative languages. We make the following contributions. First, we demonstrate that traditional MANET protocols can be expressed in a compact fashion as declarative networks. We validate these declarative protocols via an experimental study on the ORBIT wireless testbed and a cluster-based emulation environment. Second, we demonstrate that policy-driven adaptation can be specified in a generic set of declarative rule-based policies that dictate the dynamic selection of different protocols based on network conditions. Third, we conduct extensive evaluation results of declarative policy-based adaptation of MANET routing on the ORBIT wireless testbed and the cluster-based emulation environment. Our experimental results show that the specified policies enable MANETs to dynamically hybridize a variety of routing protocols to achieve a good tradeoff in bandwidth utilization and route quality.

Cologne: a declarative distributed constraint optimization platform

This paper presents Cologne, a declarative optimization platform that enables constraint optimization problems (COPs) to be declaratively specified and incrementally executed in distributed systems. Cologne integrates a declarative networking engine with an off-the-shelf constraint solver. We have developed the Colog language that combines distributed Datalog used in declarative networking with language constructs for specifying goals and constraints used in COPs. Cologne uses novel query processing strategies for processing Colog programs, by combining the use of bottom-up distributed Datalog evaluation with top-down goal-oriented constraint solving. Using case studies based on cloud and wireless network optimizations, we demonstrate that Cologne (1) can flexibly support a wide range of policy-based optimizations in distributed systems, (2) results in orders of magnitude less code compared to imperative implementations, and (3) is highly efficient with low overhead and fast convergence times.

PUMA: Policy-based Unified Multi-radio Architecture for agile mesh networking

This paper presents the design and implementation of PUMA, a declarative constraint-solving platform for policy-based routing and channel selection in multiradio wireless mesh networks. In PUMA, users formulate channel selection policies as optimization goals and constraints that are concisely declared using the Colog declarative language. To efficiently execute Colog programs in a distributed setting, PUMA integrates a high-performance constraint solver with a declarative networking engine. We demonstrate the capabilities of PUMA in defining distributed protocols that cross-optimize across channel selection and routing. We have developed a prototype of the PUMA system that we extensively evaluated in simulations and on the ORBIT testbed. Our experimental results demonstrate that PUMA can flexibly and efficiently implement a variety of centralized and distributed channel selection protocols that result in significantly higher throughput compared to single-channel and identical-channel assignment solutions.

RapidMesh: declarative toolkit for rapid experimentation of wireless mesh networks

We present the RapidMesh toolkit for rapid protocol simulation, implementation and experimentation of wireless mesh networks. RapidMesh utilizes declarative networking, a declarative, database-inspired extensible infrastructure that uses query languages to specify behavior. RapidMesh integrates a declarative networking engine with the emerging ns-3 network simulator. The same declarative specifications can also be used as actual implementations using the ns-3 network emulator, hence providing a bridge between simulation and testbed-based experimentation. We demonstrate that RapidMesh enables a variety of wireless routing protocols and neighbor discovery protocols can be synthesized via compact declarative specifications. We experimentally validate declarative MANET routing protocols in dynamic settings within RapidMesh operating in ns-3 simulation environment and on the ORBIT wireless testbed.

A policy-based constraint-solving platform towards extensible wireless channel selection and routing

This paper presents PUMA, a novel declarative constraint-solving platform that achieves efficient policy-based channel selection and routing for multi-radio wireless mesh networks. PUMA is based on declarative networking, a database-inspired extensible infrastructure using query languages to specify behavior. In PUMA, users specify high-level declarative policies that dictate their channel selection constraints and routing protocol behavior. We demonstrate that channel selection can be expressed in a compact fashion and implemented efficiently. We have developed a PUMA prototype based on the RapidNet declarative networking engine with enhancements to handle multi-channel communication and integration with an open-source constraint solver. We perform preliminary evaluation of PUMA using the emerging ns-3 network simulator, and describe our ongoing research in ORBIT testbed deployment, distributed channel selection protocols, and distributed optimizations that combine routing and channel selection.

A scalable multi-datacenter layer-2 network architecture

Cloud today is evolving towards multi-datacenter deployment, with each datacenter serving customers in different geographical areas. The independence between datacenters, however, prohibits effective inter-datacenter resource sharing and flexible management of the infrastructure. In this paper, we propose WL2, a Software-Defined Networking (SDN) solution to an Internet-scale Layer-2 network across multiple datacenters. In WL2, a logically centralized controller handles control-plane communication and configuration in each datacenter. We achieve scalability in three ways: (1) eliminating Layer-2 broadcast by rerouting control-plane traffic to the controller; (2) introducing a layered addressing scheme for aggregate Layer-2 routing; and (3) creating an overlay abstraction on top of physical topology for fast flow setup. WL2 is fault-tolerant against controller and gateway failures. We deployed and evaluated WL2 in a 2,250-VM testbed across three datacenters. The results indicate high performance and robustness of the system.