Living on the Edge: Scheduling Edge Resources Across the Cloud

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1 Living on the Edge: Scheduling Edge Resources Across the Cloud Jon Weissman Department of CS&E University of Minnesota

2 Outline Motivation New cloud models Proxy Cloud Nebula Cloud Summary A B Nebula Central

3 The Standard Cloud Data in Results out No limits Storage Computing on-demand scaling transparency

4 Consolidation Economies of scale Strong locality Appealing Features (data <-> computing) => great for analytics Novel sharing platform data/state and applications => gaming, web 2.0 Packaging Pour all tools/code/data into a VM Abstraction: connect, pour, collect

5 Cloud Landscape 50K Feet Data clouds S3, SkySurvey, GoogleHealth Compute clouds EC-2, IronScale Service clouds Gmail, Gmaps, Google-earth Specialization Non-functional: security, reliability, SLAs, cost

6 Confluence Cloud diversity and specialization => (1) no single cloud model will rule (2) new distributed models are attractive (3) emerging applications will utilize multiple clouds - multi-cloud applications

7 Multi-Cloud Applications Distributed data mining Ex: weather data + commodity prices Scientific workflows Ex: life science: GenBank<->BLAST<->PubMed, Mashups Ex: GoogleEarth + CDC pandemic data Multi-cloud parallel frameworks Ex: MapReduce across multiple data centers

8 Cloud Obstacles Clouds are centralized but the world is distributed What is distributed? clouds, data, users Distribution leads to performance, reliability, and security bottlenecks

9 good poor Google SkySurvey Amazon

10 Idea Make the cloud more distributed move it closer to data move it closer to end-users move it closer to other clouds How? exploit the rich collection of edge computers volunteers scheduling and resource selection are key

11 Two Projects Augment the Cloud with a proxy network Re-factor the Cloud to a more distributed platform

12 Proxy Network

13 Proxy Network Promote cloud <-> end-user locality cloud <-> cloud locality Via edge nodes

14 Locality Bottleneck S 1 S 2 compute on S 1 output

15 S 1 S 2 P Proxy Network

16 The Power of Proxies: Roles Cloud service interaction Proxy as a client Routing Proxy routes data to other proxies Computing Proxy executes data operators: compress, filter, merge, mine, Caching Proxy caches data (from cloud, computations, )

17 Networking Benefits Network dashboard: proxy.cs.umn.edu

18 Many better data paths Over 70% of paths can be accelerated

19 Example: Montage

20 end-user data cloud NASA Sky Survey Montage Workflow Stage 2 compute cloud Stage 1 Stage 2 Stage n.. Stage 2. Direct Path Proxy End Clients Accelerated at 3 different points

21 From SkySurvey to compute nodes

22 Inside Montage

23 From Montage to the end-user

24 Desktop User

25 Mobile user

26 Nebulas

27 Current Cloud Model Question: Are there applications that are not well suited to this cloud model? Users

28 Dispersed-Data-Intensive Services Data is geographically distributed Costly, inefficient to move to central location blog1 blog2 blog3

29 Nebula Decentralized, less-managed cloud Dispersed storage/compute resources Low user cost Users

30 How is Nebula different Cloud-oriented services impose new requirements Requirement Collective performance Locality/Contextawareness High High None Low Statefulness High/medium Low

31 Common Service Characteristics Elastic resource consumption Scale up/down based on demand Data/user distribution Execution dependent on location of data/user Limited cost May not want to pay for resources Weaker performance/robustness requirements Some failures may be ok

32 Example: blog analysis

33 Proxy Application (Web API) Data Node (FTP Server) Data Node (FTP Server) Data Node (FTP Server) Network Data N/W Data FTP Connection Node Bandwidth Updater Master Node (Java App) HTTP Request Execution Node (HTTP Server) Execution Node (HTTP Server) Execution Node (HTTP Server) DB MySQL DB

34 Results (CCE) Amazon emulator Nebula testbed Time taken (sec) # Blogs

35 Results failure Time Taken (ms) CCE - 0 Failures Nebula - 0 Failures Nebula - 1 Failure Nebula - 2 Failure Nebula - 3 Failure # Blogs

36 Trends Dynamic distributed data Mobile users Multi-cloud applications Summary Our vision of the Cloud locality of users, data, other clouds Proxy solution: less disruptive Nebulas: more radical Complementary to conventional clouds

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