BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:Asia/Kolkata X-WR-TIMEZONE:Asia/Kolkata BEGIN:VEVENT UID:54@cds.iisc.ac.in DTSTART;TZID=Asia/Kolkata:20240611T100000 DTEND;TZID=Asia/Kolkata:20240611T110000 DTSTAMP:20240604T081213Z URL:https://cds.iisc.ac.in/events/ph-d-thesis-colloquium-cds-designing-qua lity-of-service-aware-serverless-platforms/ SUMMARY:Ph.D. Thesis {Colloquium}: CDS: "Designing Quality of Service aware Serverless Platforms." DESCRIPTION:DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES\n\n\nPh.D. Thesis Colloquium\n\n\n\n\nSpeaker                 : Mr. Sheshadri Kalk unte Ramachandra\nS.R. Number         : 06-18-02-10-12-18-1-16336\nTi tle                       :  "Designing Quality of Service aw are Serverless Platforms "\nResearch Supervisor:  Dr. J. Lakshmi\nDate & amp\; Time         : June  11\, 2024 (Tuesday) at 10:00 AM\nVenue                     : The Thesis Colloquium will be held on HYBR ID Mode\n                                  # 102 CDS Sem inar Hall /MICROSOFT TEAMS.\nPlease click on the following link to join th e Thesis Colloquium:\nMS Teams link\n\n\n\n\nABSTRACT\n\nServerless Compu ting is a highly abstract computing service that allows users to design th eir applications as a workflow of independent stateless functions. The ser verless platforms provide event-driven function executions and a powerful pay-as-you-use billing model. The arduous task of function deployment\, re source provisioning\, management\, and system administration is completely undertaken by the serverless service provider\, thus providing ease of us e to the user. Though serverless platforms show many benefits and are wide ly adopted by many application domains\, they also exhibit certain shortco mings. In a bid to provide clean programming abstractions and ease of use\ , the existing platforms suffer from significant platform overheads\, lead ing to non-deterministic application execution latency. Shared resources\, independent execution of individual workflow components\, interaction bet ween various control components\, external data exchange\, etc. are some o f the major contributors to the overheads. In addition\, the prevalence of resource heterogeneity in serverless platforms\, together with the platfo rm overheads\, gives rise to variable performance in serverless function e xecutions. The varying application characteristics further add to the non- determinism of the function executions.  In this context\, Quality of Ser vice (QoS) can be an important way of conveying application requirements f or meeting its execution expectations. As QoS requirements are sensitive t o each application domain\, to understand its impact\, an exploration of h ow QoS requirements can be handled in serverless platforms is conducted in this work. The study identifies the existing literature for selecting the relevant application domains that are suitable for studying the impact of QoS requirements on resource provisioning\, instance sizing\, function de ployment decisions\, and data exchange among functions.\n\nIn the first ph ase\, we examine the domain of Image and Video analytics. The applications in this domain are typically deployed in a heterogeneous resources settin g akin to the Edge-Cloud continuum. With varying application input size\, it is imperative to select resource assignments to functions that meets us er-specified QoS requirements. However\, in a heterogeneous resource pool comprising Edge and Cloud resources\, choosing a resource layer and functi on resource size that is both cost-efficient and one that meets QoS requir ements is a challenging task. In order to address this issue\, we present a novel QoS-aware serverless platform that deduces function resource speci fication in a heterogeneous resource setting. The proposed platform perfor ms function placement across Edge and Cloud layers based on incoming input size and user-specified QoS requirements while prioritizing low-cost func tion executions. Experimental results based on real-world workloads on a v ideo surveillance application show that the proposed platform brings effic ient resource utilization and cost savings at the Cloud by reducing the re source usage by up to 30%.\n\nIn the second phase\, we examine the domain of Network Function Virtualization.  Network Function Virtualization (NFV ) and Software Defined Networks (SDNs) allow the network functions to be p rogrammed as software entities that can be deployed on commodity servers i n the Cloud\, referred to as Virtual Network Functions (VNFs). VNFs are ar ranged in a workflow to enforce a network policy referred to as Service Fu nction Chain (SFC). Existing solutions examine the SFC deployment on eithe r IaaS or FaaS offerings. IaaS solutions alone lack the dynamism to respon d to quick workload changes for network traffic which is similar to stream ing data. Existing FaaS solutions exhibit significant platform overheads w hich are prohibitive to meet the application's requirements. Further\, the variability in the incoming flowlet and payload sizes of applications exa cerbates the problem of selecting function resource assignments that both satisfy QoS requirements and one that results in low resource usage. In or der to address these shortcomings\, we propose a Hybrid Serverless Platfor m (HSP) encompassing IaaS and FaaS in its function deployment strategy. Sp ecifically\, The IaaS components handle the steady state load\, whereas th e FaaS components activate during the dynamic change associated with scali ng to minimize service loss. The proposed HSP controller takes resource pr ovisioning decisions based on user-specified QoS requirements and the appl ication's flow statistics. The HSP controller's design exploits data local ity in SFC realization\, reducing data-transfer times and platform overhea ds between VNFs. The proposed platform provides up to 35% resource savings as compared to a pure IaaS deployment and up to 55% lower end-to-end SFC execution times as compared to a baseline FaaS implementation with minimal loss of flowlet service.\n\nIn the third phase\, we examine the domain of Web Inferencing which constitutes an important class of event-driven appl ications that lend themselves to being composed as a workflow of functions . Typically\, web inferencing applications are deployed across a heterogen eous setting comprising Edge and Cloud resources. Though web inferencing w orkflows have seen an extensive adoption of serverless computing\, they su ffer from the overheads of the serverless computing platforms\, which incr eases the application's end-to-end latency. Existing literature addresses the problem of high platform overheads by a technique called 'Function Fus ion'\, which combines consecutive serverless functions in a workflow into a single logical group. However\, existing solutions are limited by the pe ak resource sizes of functions that dictate the sizing of fusion groups\; they are insensitive to the varying application inputs and QoS requirement s of the inferencing applications. In order to address these issues\, we p ropose a novel fusion criteria called 'RightFusion' that performs cost-eff icient function fusion in serverless platforms that manage a heterogeneous resource pool. The proposed platform uses incoming application characteri stics and user-specified QoS requirements to dynamically arrive at functio n fusion decisions that are both cost-efficient and QoS-abiding. Experimen tal evaluation of representative inferencing applications shows that Right Fusion reduces resource usage by above 35% at Edge and Cloud while meeting the QoS requirements compared to the PeakFusion baseline.\n\nIn conclusio n\, this study demonstrates the value of considering application QoS in se rverless computing. The QoS specifications enable the platform to undertak e resource management and function placement decisions that meet user expe ctations. In our studies\, QoS requirements from different application dom ains have translated to different design decisions that address various pr oblems\, including resource right-sizing\, function fusion\, request order ing\, etc.\, resulting in cost and resource savings. Current Serverless pl atforms take off the burden of resource provisioning and placement for exe cution from the user. However\, they are agnostic to the expectations of a pplications. Applications\, on the other hand\, suffer from non-determinis tic overheads from these platforms. Given the differences in differing app lications\, QoS provides a mechanism to express application requirements t hat the serverless platform can use for decision-making with regard to app lication execution. The current exploration exposes that QoS is applicatio n-specific and requires different methods to deal with it\; emphasizing th e need for customization in serverless platform design. It also brings to the fore the value of considering the integration of learning approaches i n serverless controller's decision-making. This study considered cost and performance as the primary QoS attributes for each of the domains examined . Other QoS features\, like security\, privacy\, reliability\, jurispruden ce\, etc.\, are yet to be explored.\n\n\n\n\n\n\n\nALL ARE WELCOME CATEGORIES:Events,Ph.D. Thesis Colloquium END:VEVENT BEGIN:VTIMEZONE TZID:Asia/Kolkata X-LIC-LOCATION:Asia/Kolkata BEGIN:STANDARD DTSTART:20230612T100000 TZOFFSETFROM:+0530 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE END:VCALENDAR