This paper presents the design and implementation of PUMA, a declarative constraint-solving platform for policy-based routing and channel selection in multi-radio wireless mesh networks. In PUMA, users formulate channel selection policies as optimization goals and constraints that are concisely declared using the PawLog declarative language. To efficiently execute PawLog 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.

This paper presents PUMA, a novel declarative constraintsolving platform that achieves efficient policy-based channel selection and routing for multi-radio wireless mesh networks. PUMA is based on declarative networking, a databaseinspired 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.

This paper presents the design and implementation of PUMA, a declarative constraint-solving platform for policy-based routing and channel selection in multi-radio wireless mesh networks. In PUMA, users formulate channel selection policies as optimization goals and constraints that are concisely declared using the PawLog declarative language. To efficiently execute PawLog 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.

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We propose the demonstration of SP4, a software-based programmable packet processing platform that supports (1) stateful packet processing useful for analyzing traffic flows with session semantics, (2) uses a task-stealing architecture that automatically leverages multi-core processing capabilities in a load-balanced manner without the need for explicit performance profiling, and (3) a declarative language for rapidly specifying and composing new packet processing functionalities from reusable modules. Our demonstration showcases the use of SP4 for performing high-throughput analysis of traffic traces for a variety of applications, such as filtering out unwanted traffic and detection of DDoS attacks using machine learning based analysis.