http://link.springer.com/chapter/10.1007%2F978-3-540-88875-8_108
This paper introduces an approach for abstracting access to functionality in Pervasive Computing systems where very different types of devices co-exist. Tiny, resource-poor 8-bit based wireless embedded sensor nodes use highly fragmented programming, with code distributed over possibly hundreds of nodes. More powerful devices as mobile, handled devices, laptops or even server use coarse-grained distribution. The Implicit Middleware approach provides a way to both unify and simplify middleware for Pervasive Computing systems, by means of transparently distributing functionality in the system and making them context aware. The approach ensures optimized run-time behavior and adaptation to the system landscape. We also present an implementation using the XMLVM representation for code generation, and an evaluation running on PCs, J2ME CLDC 1.0 compatible 32Bit sensor nodes and 8Bit-MCU based nodes with an optimized light-weight VM.
Impact of Soft Errors in Silicon on Reliability and Availability of ServersIshwar Parulkar
Presentation deals with manifestation of silicon soft errors at system level. System level failure targets and a quantitative sense of trade-offs in soft error protection in servers is described. Slides are from an invited talk given at an "Innovative Practices" session on system reliability at VTS 2006.
Impact of Soft Errors in Silicon on Reliability and Availability of ServersIshwar Parulkar
Presentation deals with manifestation of silicon soft errors at system level. System level failure targets and a quantitative sense of trade-offs in soft error protection in servers is described. Slides are from an invited talk given at an "Innovative Practices" session on system reliability at VTS 2006.
Overview of EJB technology.
Enterprise Java Beans (EJB) is a server-side component technology for Java EE based systems (JEE).
Beans are business logic components that implement a standard interface through which the bean is hooked into the bean container (= runtime object for bean).
A Java class implementing one of the standard bean interfaces is an Enterprise Java Bean. Beans can be accessed remotely, usually from a client tier.
The EJB standard was developed to provide a common framework for solving recurring problems in business application development like persistence, transactions,
security and runtime and lifecycle management. The EJB standard evolved greatly over time. EJB version 1 and 2 were complex and required to implement many interfaces
and exception handling in EJBs. EJB version 3 brought great simplifications and did away with interfaces by replacing these with annotations which provide greater flexibility while keeping complexity low. EJBs come in 3 different flavors: Stateless and stateful session beans and message driven beans. Entity beans of EJB version 1 and 2 were replaced by the Java Persistence API in EJB version 3.
Thesis presentation: Middleware for Ubicomp - A Model Driven Development Appr...Till Riedel
With computers that will be interwoven into almost every industrial product like its nervous system (Steinbuch, 1966) we are already approaching what Weiser (1991) called Ubiquitous Computing, in terms of quantity, degree of embedding of computing systems in our life and work environment.
This thesis investigates model driven software development (MDSD) approach as a tool for contextual adaption of ubiquitous systems. Ubiquitous Systems (i.e. the embedded devices) are subject to changes that affect the execution of software. The systems are very heterogeneous and and the designer has to take a diverse set of plattforms and ressource constrained hardware into consideration.
By implementing a model driven development techniques for core problems of ubiquitous computing, namely distributed execution and heterogeneous communication in ubiquitous systems the work demonstrates that Model Driven Software Development of Ubiquitous Systems maybe used to solve the inherent contradiction between top-down and bottom-up development of networked embedded systems.
Cloud initiatives are beginning to dominate enterprise IT roadmaps. Successful adoption of Cloud and the subsequent governance challenges warrant a Cloud reference architecture that is applied consistently across the enterprise. This presentation will answer questions such as what exactly a Cloud is, why you need it, what changes it will bring to the enterprise, and what the key capabilities of a Cloud infrastructure are - using Oracle's Cloud Reference Architecture, which is part of the IT Strategies from Oracle (ITSO) Cloud Enterprise Technology Strategy (ETS).
System model optimization through functional models execution methodology and...Daniele Gianni
Presentation delivered at the 3rd IEEE Track on
Collaborative Modeling & Simulation - CoMetS'12.
Please see http://www.sel.uniroma2.it/comets12/ for further details.
Towards Enterprise Interoperability Service UtilitiesBrian Elvesæter
B. Elvesæter, F. Taglino, E. D. Grosso, G. Benguria and A. Capellini, “Towards Enterprise Interoperability Service Utilities”, paper presentation at IWEI 2008, Munich Germany, 18 September 2008.
Overview of EJB technology.
Enterprise Java Beans (EJB) is a server-side component technology for Java EE based systems (JEE).
Beans are business logic components that implement a standard interface through which the bean is hooked into the bean container (= runtime object for bean).
A Java class implementing one of the standard bean interfaces is an Enterprise Java Bean. Beans can be accessed remotely, usually from a client tier.
The EJB standard was developed to provide a common framework for solving recurring problems in business application development like persistence, transactions,
security and runtime and lifecycle management. The EJB standard evolved greatly over time. EJB version 1 and 2 were complex and required to implement many interfaces
and exception handling in EJBs. EJB version 3 brought great simplifications and did away with interfaces by replacing these with annotations which provide greater flexibility while keeping complexity low. EJBs come in 3 different flavors: Stateless and stateful session beans and message driven beans. Entity beans of EJB version 1 and 2 were replaced by the Java Persistence API in EJB version 3.
Thesis presentation: Middleware for Ubicomp - A Model Driven Development Appr...Till Riedel
With computers that will be interwoven into almost every industrial product like its nervous system (Steinbuch, 1966) we are already approaching what Weiser (1991) called Ubiquitous Computing, in terms of quantity, degree of embedding of computing systems in our life and work environment.
This thesis investigates model driven software development (MDSD) approach as a tool for contextual adaption of ubiquitous systems. Ubiquitous Systems (i.e. the embedded devices) are subject to changes that affect the execution of software. The systems are very heterogeneous and and the designer has to take a diverse set of plattforms and ressource constrained hardware into consideration.
By implementing a model driven development techniques for core problems of ubiquitous computing, namely distributed execution and heterogeneous communication in ubiquitous systems the work demonstrates that Model Driven Software Development of Ubiquitous Systems maybe used to solve the inherent contradiction between top-down and bottom-up development of networked embedded systems.
Cloud initiatives are beginning to dominate enterprise IT roadmaps. Successful adoption of Cloud and the subsequent governance challenges warrant a Cloud reference architecture that is applied consistently across the enterprise. This presentation will answer questions such as what exactly a Cloud is, why you need it, what changes it will bring to the enterprise, and what the key capabilities of a Cloud infrastructure are - using Oracle's Cloud Reference Architecture, which is part of the IT Strategies from Oracle (ITSO) Cloud Enterprise Technology Strategy (ETS).
System model optimization through functional models execution methodology and...Daniele Gianni
Presentation delivered at the 3rd IEEE Track on
Collaborative Modeling & Simulation - CoMetS'12.
Please see http://www.sel.uniroma2.it/comets12/ for further details.
Towards Enterprise Interoperability Service UtilitiesBrian Elvesæter
B. Elvesæter, F. Taglino, E. D. Grosso, G. Benguria and A. Capellini, “Towards Enterprise Interoperability Service Utilities”, paper presentation at IWEI 2008, Munich Germany, 18 September 2008.
What are the actors? What are they used for? And how can we develop them? And how are they published and used on Azure? Let's see how it's done in this session
I translate Framework Design Guideline to Korean.
This Book is very impressed to me.
So I want to share Krzysztof Cwalina's Knowledge.
I re-edit his presentation and add my opinion.
Interoperability for Intelligence Applications using Data-Centric MiddlewareGerardo Pardo-Castellote
Presentation at the May 2012 Intelligence Workshop held in Rome Italy.
Interoperability is key to reducing cost in the development and maintenance of applications that span multiple providers or must be supported over long periods of time. This presentation describes the role of network middleware technologies in such systems and how the use of a data-centric middleware, such as OMG DDS, makes developing such systems easier and more cost-effective.
Lambda Architecture 2.0 Convergence between Real-Time Analytics, Context-awar...Sabri Skhiri
At Huawei, we have developed a scalable Complex Event Processing with a significant improvement of the expressiveness. In the scope of the "context-aware" distributed systems, we need to define new architecture patterns. In this way we open new doors to new features and capabilities.
From Load Forecasting to Demand Response - A Web of Things Use CaseTill Riedel
This paper provides a Web of Things use case from a personalized load forecasting service to a gamied demand response program. Combining real-world measuring applications with web-based applications opens new opportunities to the smart grid. For this purpose, we propose a Web of Things framework for a novel load forecasting process at the appliance level. Firstly, we illustrate the concept design of the Web of Things framework consisting of the sensing infrastructure,
the activity recognition and the load forecasting modules.
Secondly, we show how we guarantee the modularity and flexibility for implementing all the three modules in a web-
based manner. On top of our infrastructure, we propose an
extended Web of Things use case by integrating our load
forecasting approach into a demand response concept.
Structuring Big Data results to create new information: Smart Data. These Smart Data can be used to advance knowledge and support decision-making processes.
A close cooperation between industry and science creates better conditions for cutting-edge research in Data Engineering/Smart Data.
A dialectic perspective on the future of ubicomp. My contribution to panel discussion with Daniel Roggen and Romit Roy Choudhury. For more infos goto cosdeo.teco.edu
uBox A Distributed Resource Management Architecture for the Web-of-ThingsTill Riedel
Although there are many smart devices and networked embedded object applications usingWorld WideWeb technologies, it is still a big step to go towards a true Web of Things. It is e.g. difficult to build ubiquitous WoT applications that work in and accross multiple environments. Approaches which aggregate WoT ressources by centralizing all the resource information, have problems: total dependency on external infrasture, lack of private WoT management, inflexible communication patterns and limited dynamic ressource discovery and mapping. To solve these problems, we propose uBox, a localWoT platform which can be a stand-alone server to make your WoT environment, with interfaces to connect the other local WoT platforms. This way, which we call uBoXing, we can create World Wide WoT platform with a distributed architecture. This paper describes the concept of a distributed resource management architecture, and how we implement the concept into software. Also, we will discuss the platform with the example application in SmartTecO environment.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
2. Motivation
Information systems Information
Files
Data bases
Object-ID State Processes
Barcode RFID Sensor Smart
Manual scanning Tags networks Items
Accumulation
Real world Objects, items, activities, events
Control of complex information flows between
processes in the real world and computer-based
information systems.
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 2
3. Motivation: CoBis
Business Logic describes the real world
processes in a virtual representation
Interfaces needed to couple real and virtual
world and keep consistency
Smart Items:
deploy business logic on sensor nodes
Example CoBIs:
SAP Environment Health and Safety (EH&S)
Sensor Nodes on Chemical Drums
Storage Regulations Detection Services:
Storage Incompatibility
Absolute volume limit
Temperature / Environmental constraints
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 3
4. Relocation of Services
B u s in e s s L o g ic B a c k e n d
Task
S e n s o r N e tw o rk R e lo c a te d
Relocated Task
Task
C o lla b o r a tiv e B u s in e s s
Ite m s
Challenge:
Integration Sensing Services in Application Framework
Problems:
How to provide syntactically and semantically equal Interfaces?
How to integrate into development process?
How much of the code to execute on “the Node”?
How to partition (existing) Services?
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 4
5. Design of an Implicit Middleware
How much of code to execute on “the node”?
Development date != deployment date
Changing Hardware
Advances in Hardware
Use of more constraint/cheaper HW
Changing Constraints
Lifetime/energy saving constraints differ per application (not per service)
Changing Networking/topologies
Based on local necessities, link costs vary with topologies (1 vs. n hop)
Networks with hybrid nodes: more powerful router/gateway nodes
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 5
6. Design of an Implicit Middleware
How to partition (existing) Services?
Maintain semantics of existing Service (Middleware):
Location transparency
Access transparency
Concurrency transparency
Failure transparency *
Technology transparency
Adding Middleware adds new abstractions:
use VM semantics instead !!
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 6
7. Implicit Middleware Work-flow
Generating the optimal distribution of an application/service
Optimality based on model !
Just before deployment
Implementation optimizes execution times
network
instruction
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 7
8. Transformation Architecture
System
Java App/Service Platform Models
Landscape
Simulation Monitoring
Trace Model System Model
Byte-Code Optimization Problem
Transformation
Optimization
Allocation
Model
Distributed App
Deployment
Instantiation
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 8
9. Modeling Software and System
System
Java App/Service Platform Models
Landscape
Simulation Monitoring
Trace Model System Model
Optimization Problem
Allocation
Model
Distributed App
Deployment
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 9
10. System/Trace Model
System Model
References Platform Model System
Platform Models
Landscape
Contains cost functions/parameters
User defined/from simulation
Generated from Node Discovery System Model
Trace Model
Use Eclipse Test and Performance Tools
Generates ecore model
Use simulated inputs
Currently by random distribution Monolithic Java App
Set of simulated runtime libraries
Execute program locally
Trace Model
Approximate
average execution time of Class A
average number of calls from Class A to B
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 10
11. Optimization
System
Java App/Service Platform Models
Landscape
Trace Model System Model
Optimization Problem
Optimization
Allocation
Model
Distributed App
Deployment
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 11
12. Optimization
Trace Model System Model
Generate formal ILP Problem that
assigns all classes to a Platform
Optimization Problem
( is the allocation relation to be found) Optimization
while minimizing communication Allocation
Model
and execution costs
is a product :(
Sensor Classes and immovable interfaces
are fixed:
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 12
13. Byte-Code Transformation
System
Java App/Service Platform Models
Landscape
Trace Model System Model
Byte-Code Optimization Problem
Transformation
Allocation
Model
Distributed App
Deployment
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 13
14. Byte-Code Transformation
1st Stage: Partitioning
Generate platform Monolithic Java App
independent middleware code
Allocation Model
2 Stage:
nd
Target code generation Distributed App
Use of XSLT technology
Principal support for arbitrary
target language
Proof of concept javascript/C++
targets
Uses either ASM or XMLVM for
Example: computationally heavy or code analysis/rewriting
classes w/ WS interface
Transformations build to
retain code semantics
Statical analysis and
rewriting/code generation on
byte code/XMLVM level
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 14
15. Stub and Dispatcher Generation
Generated class stubs replace remote classes
Interface to middleware runtime
Connects local and remote garbage collection
Generated dispatcher
No runtime reflection
Perfect hash (possible because of late optimization)
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 15
16. Transparent Distribution
Stubs call Middleware to marshal calls
Simple push interface
Type safe for basic data types
Objects are passed by reference
Add fixed class and method id
Dispatch calls method by id
pops arguments from message
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 16
17. Runtime Architecture
Generi
c
Portabl
e Specifi
c
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 17
18. Instantiation
System
Java App/Service Platform Models
Landscape
Trace Model System Model
Optimization Problem
Allocation
Model
Distributed App
Deployment
Instantiation
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 18
19. Deployment: Java on Particles/Sun Spots
Ultra light-weight Java VM on Particle computers
Further size and static optimizations on byte code level
Platform Independent CLDC 1.1 Java
Java ByteCode for Sun Spots
Strip down,
optimization, versioning Java
Virtual Machine
Wireless
Java ByteCode Transfer
for Particles
Versioning control,
Selective updates, Particle Computer
Mass programming
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 19
20. Optimization Results
Optimizing only for call latencies
Optimizing only for execution times
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 20
21. Performance
Optimizer (Simple Vibration Alarm Example)
Using ZIMPL Interface: 342 variables and 980 constraints
Solved 0.2s on 1.65GHz x86 CPU by soPlex solver
Branch and Bound
Called once on deployment
Middleware Overhead
Particle Computer
Low execution overhead (typ. <1ms per call vs. 13ms RF slot)
Low memory overhead (in bytes):
Sun Spots
Stub w/ Methods: code size 4,13 kByte
High overhead due to thread generation (round trip >500 ms!!!)
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 21
22. Limitations/Discussion I
More complex cost models?
Trace model based
Also becomes more difficult to model
Exhaustive search
implemented but slow
Possible heuristics are questionable
Describe as non-linear (convex) optimizations
does also not describe most network effects
Simulation in the loop
Easy integrability
All VM based
Simulator hooks can be generated
Really costly!
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 22
23. Limitations/Discussion II
Finer granularity for partitioning?
Object mobility
Probably needed for realistic apps
Stubs for all classes
Synchronization overhead = more runtime middleware
Efficient only with more statical analysis (data flow)
Function level
Need to expose internal state
Instruction level
More difficult to retain semantics
Distributed VM
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 23
24. Conclusion
Solution for easy development of “smart item” technology (1-click)
Optimizes partitioning between hybrid devices
Based on device capabilities
Network properties
Implementation using generative model based approach
Minimal runtime requirements
No reflection / efficient platform independent code
Support for energy efficient Particle sensor nodes and CLDC 1.1
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 24
25. Future Directions
Integration in Deployment Framework like OSGi
Run Implicit Middleware as container/host
rOSGi synergies?
Start directly from Abstract Models
Does not require “reverse” engineering of classes
System already nicely integrates in EMF Toolchain
Build better models for simulation aspects
Integrate e.g. performance measures earlier in development process
Support for distributed sensor networking
Capture semantics of context
Move away from pure Java semantics
Support parallel aggregating/redundant operations with variable # of
nodes
Till Riedel , TecO Persys'08, Monterrey, 14.11.2008 25