NetQoPE: A Middleware-based Netowork QoS Provisioning Engine for Distributed Real-time and Embedded Systems Jaiganesh Balasubramanian Work done in collaboration with Sumant Tambe, Aniruddha Gokhale & Doug Schmidt (Vanderbilt) Srirang Gadgil, Frederic Porter & Dasarathy Balakrishnan (Telcordia) ISIS, Dept. of EECS Vanderbilt University Nashville, Tennessee May 3, 2007 CS WithIt Seminar

2 Distributed Real-time & Embedded (DRE) Systems Network-centric and large-scale “systems of systems” –e.g., industrial automation, emergency response Satisfying tradeoffs between multiple (often conflicting) QoS demands –e.g., secure, real-time, reliable, etc. Regulating & adapting to (dis)continuous changes in runtime environments e.g., online prognostics, dependable upgrades, keep mission critical tasks operational, dynamic resource mgmt DRE systems developed via robust and reliable system composition and integration of services and applications

3 Variability in the solution space (systems integrator role) Diversity in platforms, languages, protocols & tool environments Enormous accidental & inherent complexities Continuous evolution & change Challenges in Realizing DRE Systems Variability in the problem space (domain expert role) Functional diversity Composition, deployment and configuration diversity QoS requirements diversity Mapping problem artifacts to solution artifacts is hard

4 Case Study: Modern Office Environment Office traffic operates over IP networks & Fast ethernets Multiple application flows: Videoconferencing Sensory (e.g., fire alarms) Differing QoS requirements Fire alarm – highest priority Videoconf – multimedia – best effort QoS provisioned using DiffServ Network QoS Provisioning Steps 1.Specify network QoS requirements for each application flow 2.Allocate network-level resources and DiffServ Code Points (DSCP) for every application flow joining two end points 3.Mark outgoing packet with the right DSCP values

5 Challenge 1: QoS Requirements Specification x

6 Challenge 2: Network Resource Allocation x

7 Challenge 3: Runtime Network QoS Settings x

8 NetQoPE Multistage Architecture Stage 1 Capabilities for intuitive and scalable network QoS specification Stage 2: Capabilities for resource allocation and configuration Stage 3: Capabilities for runtime support for QoS settings enforcement

9 Stage 1 : Model Driven Engineering Office Scenario Server room to control room is HP Parking lot to control room is Videoconferencing is MM Temperature sensor is HR Model Driven Engineering solution Component QoS Modeling Language Provides intuitive abstractions to specify QoS Scalable solutions Developed in GME Network QoS modeling allows modeling QoS per application flow Classification into high priority (HP), high reliability (HR), multimedia (MM) and best effort (BE) classes Enables bandwidth reservation in both directions Client propagated or server declared models

10 Stage 2: Resource Allocator Engine xyz

11 Stage 3: Runtime Policy Framework xyz

12 Evaluating NetQoPE Experimental Setup ISISlab setup blade servers running Fedora core DiffServ QoS over IP Networks Telcordia Bandwidth Broker Objectives (describe in one line what the 3 eval criteria are)

13 Results 1: Measuring Runtime Overhead Rationale Observations Analysis

14 Results 2: QoS Customization Capabilities Rationale Observations Analysis

15 Results 3: Admission Control Capabilities Rationale Observations Analysis

16 Concluding Remarks Multiple levels of abstraction required for resolving tangling of QoS issues Need expressive power to define QoS intent in the problem space, and perform design-time analysis