Heading Off Correlated Failures through Independence-as-a-Service
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- Marcia Juliana Richards
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1 Heading Off Correlated Failures through Independence-as-a-Service Ennan Zhai 1 Ruichuan Chen 2, David Isaac Wolinsky 1, Bryan Ford 1 1 Yale University 2 Bell Labs/Alcatel-Lucent
2 Background Cloud services ensure reliability by redundancy: - Amazon S3 replicates data on multiple racks - icloud rents EC2 and Azure redundantly
3 Background Cloud services ensure reliability by redundancy: - Amazon S3 replicates data on multiple racks - icloud rents EC2 and Azure redundantly
4 Background Cloud services ensure reliability by redundancy: - Amazon S3 replicates data on multiple racks - icloud rents EC2 and Azure redundantly
5 Background Cloud services ensure reliability by redundancy: - Amazon S3 replicates data on multiple racks - icloud rents EC2 and Azure redundantly Unexpected common dependencies!
6 Service Outage Losses Data Center Outages Generate Big Losses Downtime in a data center can cost an average of $505,500 per incident, according to a Ponemon Institute study. Analytics Slideshow: 2010 Data Center Operational Trends Report
7 Service Outage Losses Data Center Outages Generate Big Losses Downtime in a data center can cost an average of $505,500 per incident, according to a Ponemon Institute study. Analytics Slideshow: 2010 Data Center Operational Trends Report
8 What is correlated failure?
9 What is correlated failure? Rack1 Rack2 Rack3 Switch1 Switch2 Switch3
10 What is correlated failure? Rack1 Rack2 Rack3 Primary Backup Backup Switch1 Switch2 Switch3
11 What is correlated failure? Rack1 Rack2 Rack3 Primary Backup Backup Switch1 Switch2 Switch3 Agg Switch
12 What is correlated failure? Rack1 Rack2 Rack3 Primary Backup Backup Switch1 Switch2 Switch3 Agg Switch
13 What is correlated failure? Rack1 Rack2 Rack3 Primary Backup Backup Switch1 Switch2 Switch3 Agg Switch
14 Realistic Example
15 Realistic Example Correlated failures resulting from EBS due to bugs in one EBS server Summary of the October 22, 2012 AWS Service Event in the US-East Region We d like to share more about the service event that occurred on Monday, October 22nd in the US-East Region. We have now completed the analysis of the events that affected AWS customers, and we want to describe what happened, our understanding of how customers were affected, and what we are doing to prevent a similar issue from occurring in the future. The Primary Event and the Impact to Amazon Elastic Block Store (EBS) and Amazon Elastic Compute Cloud (EC2)
16 Realistic Example Elastic Compute Cloud (EC2) Elastic Block Store (EBS)
17 Realistic Example Elastic Block Store (EBS)
18 Realistic Example VM1 VM2 VM1 VM3 VM1 VM2 VM3 VM Elastic Block Store (EBS)
19 Realistic Example VM1 VM2 VM1 VM3 VM1 VM2 VM3 VM EBS Server1 EBS Server2
20 Realistic Example VM1 VM2 VM1 VM3 VM1 VM2 VM3 VM EBS Server1 EBS Server2
21 Realistic Example VM1 VM2 VM1 VM3 VM1 VM2 VM3 VM EBS Server1 EBS Server2
22 Realistic Example VM1 VM2 VM1 VM3 VM1 VM2 VM3 VM EBS Server1 EBS Server2
23 Even Worse
24
25 Video App Cloud Provider A Cloud Provider B
26 Video App Cloud Provider A Cloud Provider B Third-party infrastructure components
27 Video App Cloud Provider A Cloud Provider B Third-party infrastructure components ISP Router A ISP Router B ISP Router C
28 Video App Cloud Provider A Cloud Provider B Third-party infrastructure components ISP Router A ISP Router B ISP Router C Power Source
29 Video App Cloud Provider A Cloud Provider B Third-party infrastructure components ISP Router A ISP Router B ISP Router C Power Source
30 Video App Cloud Provider A Cloud Provider B Third-party infrastructure components ISP Router A ISP Router B ISP Router C Power Source
31 Video App Cloud Provider A Cloud Provider B Cloud providers do not usually share Third-party infrastructure components information about their dependencies ISP Router A ISP Router B ISP Router C Power Source
32 Existing Efforts Cloud providers allocate or tolerate failures via: - diagnosis systems; - fault-tolerant systems.
33 Existing Efforts Cloud providers allocate or tolerate failures via: - diagnosis systems; - fault-tolerant systems. Solving the problem after outage occurs. We want to prevent the problem before the outage occurs.
34 Existing Efforts Cloud providers allocate or tolerate failures via: - diagnosis systems; - fault-tolerant systems. Solving the problem after outage occurs. Prevent correlated failures before outage occurs.
35 Existing Efforts Cloud providers allocate or tolerate failures via: - diagnosis systems; - fault-tolerant systems. Solving the problem after outage occurs. Prevent correlated failures before outage occurs. Independence-as-a-Service (INDaaS)
36 INDaaS Workflow Service Provider, Alice INDaaS A Given Redundancy Configuration
37 INDaaS Workflow Service Provider, Alice INDaaS Two-Way Redundancy Configuration Dependency Data Source1 Dependency Data Source2
38 INDaaS Workflow Service Provider, Alice Independence of this two-way redundancy? INDaaS Two-Way Redundancy Configuration Dependency Data Source1 Dependency Data Source2
39 INDaaS Workflow Service Provider, Alice Step1: Specification Submission INDaaS Dependency Data Source1 Dependency Data Source2
40 INDaaS Workflow Service Provider, Alice Step1 INDaaS Step2: Dependency data collection Dependency Data Source1 Step2: Dependency data collection Dependency Data Source2
41 INDaaS Workflow Service Provider, Alice Step1 Step3: Independence Evaluation INDaaS Step2 Step2 Dependency Data Source1 Dependency Data Source2
42 INDaaS Workflow Service Provider, Alice Relative Independence is 0.3 Step1 Step3 INDaaS Step2 Step2 Dependency Data Source1 Dependency Data Source2
43 Multiple Cloud Providers Service Provider, Alice Step1 Step3 INDaaS Step2 Step2 Dependency Data Source1 Dependency Data Source2
44 Multiple Cloud Providers Service Provider, Alice Step1 Step3 Unwilling to share the dependency data INDaaS Step2 Step2 Unwilling to share the dependency data Data Source1 (Cloud1) Data Source2 (Cloud2)
45 Private Independence Evaluation Service Provider, Alice Step1 INDaaS Step2 Data Source1 (Cloud1) Step3: Private auditing Step2 Data Source2 (Cloud2)
46 Private Independence Evaluation Service Provider, Alice Step1 INDaaS Step2 Step4 Step4 Step2 Data Source1 (Cloud1) Step3 Data Source2 (Cloud2)
47 Private Independence Evaluation Service Provider, Alice Step1 Only know my information Step2 Step4 INDaaS Step4 Step2 Only know my information Data Source1 (Cloud1) Step3 Data Source2 (Cloud2)
48 Private Independence Evaluation Service Provider, Alice Only the relative independence Step1 INDaaS Step2 Step4 Step4 Step2 Data Source1 (Cloud1) Step3 Data Source2 (Cloud2)
49 Private Independence Evaluation Service Provider, Alice Step1 Step5 INDaaS Step2 Step4 Step4 Step2 Data Source1 (Cloud1) Step3 Data Source2 (Cloud2)
50 Technical Challenges Step1 Step5 INDaaS Step2 Step4 Step4 Step2 Dependency Data Source1 Step3 Dependency Data Source2
51 Technical Challenges #1: Dependency collections - Solution: Reusing existing tools Step1 Step5 INDaaS Step2 Step4 Step4 Step2 Dependency Data Source1 Step3 Dependency Data Source2
52 Technical Challenges #1: Dependency collections - Solution: Reusing existing tools Step1 INDaaS Step5 #2: Dependency representation - Solution: Fault graphs Step2 Step4 Step4 Step2 Dependency Data Source1 Step3 Dependency Data Source2
53 Technical Challenges #1: Dependency collections - Solution: Reusing existing tools Step2 Step1 Step5 INDaaS Step4 Step4 Step2 #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm Dependency Data Source1 Step3 Dependency Data Source2
54 Technical Challenges Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
55 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
56 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
57 Dependency Data Collections Reuse existing data collection tools: - Convert the outputs to uniform format. - Three types of format: NET, HW and SW. Our defined format Type Network Hardware Software Dependency Expression <src= S dst= D route= x,y,z /> <hw= H type= T dep= x /> <pgm= S hw= H dep= x,y,z /> Please see our paper for more details
58 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
59 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
60 Example Redundancy
61 Example Redundancy
62 Example Redundancy SW HW NET
63 Building Fault Graph Top-to-Bottom SW HW NET
64 Step1: Root Node Redundancy configuration fails
65 Step2: Server Nodes Redundancy configuration fails Server 1 fails Server 2 fails
66 Step2: Server Nodes Redundancy configuration fails Server 1 fails Server 2 fails AND gate: all the sublayer nodes fail, the upper layer node fails
67 Step3: Dependency Nodes Redundancy configuration fails Server 1 fails Server 2 fails +" +" HW fails Net fails SW fails Net fails SW fails HW fails
68 Step3: Dependency Nodes Redundancy configuration fails Server 1 fails Server 2 fails +" +" HW fails Net fails SW fails Net fails SW fails HW fails OR gate: one of the sublayer nodes fails, the upper layer node fails
69 Step4: Hardware Dependency Redundancy configuration fails Server 1 fails Server 2 fails +" +" HW fails Net fails SW fails Net fails SW fails HW fails +" +" CPU1 Disk1 CPU2 Disk2
70 Step5: Network Dependency Redundancy configuration fails Server 1 fails Server 2 fails +" +" HW fails Net fails SW fails Net fails SW fails HW fails +" +" CPU1 Disk1 Path1 Path2 CPU2 Disk2 Core1 +" +" ToR1 Core2
71 Step6: Software Dependency Redundancy configuration fails Server 1 fails Server 2 fails +" +" HW fails Net fails SW fails Net fails SW fails HW fails +" CPU1 Disk1 Path1 Path2 Riak +" Query CPU2 +" Disk2 +" +" +" +" Core1 ToR1 Core2 libsvnl libc6 libccl
72 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
73 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
74 Efficient Auditing Two algorithms balancing cost and accuracy: - Minimal fault set algorithm - Failure sampling algorithm
75 Efficient Auditing Two algorithms balancing cost and accuracy: - Minimal fault set algorithm - Failure sampling algorithm
76 Minimal Fault Set Algorithm Traditional algorithm in safety engineering - Exponential complexity (NP-hard) We are the first to apply it in Cloud area: - Analyzing a fat tree with 30,528 with ~40 hours
77 Minimal Fault Set Algorithm Traditional algorithm in safety engineer - Exponential complexity (NP-hard) We are the first to apply it in Cloud area: - Analyzing a fat tree with 30,528 with ~40 hours We propose efficient failure sampling algorithm.
78 Failure Sampling Algorithm Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails
79 Failure Sampling Algorithm Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails 1 or 0 1 or 0 1 or 0
80 Failure Sampling Algorithm Redundancy configuration fails 1 or 0? Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails 1 or 0 1 or 0 1 or 0
81 Failure Sampling Algorithm Redundancy configuration fails 1 or 0? Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails 1 or 0 1 or 0 1 or 0 Fault Sets
82 The 1st Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails Fault Sets
83 The 1st Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails 1 or 0 1 or 0 1 or 0 Fault Sets
84 The 1st Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails
85 The 1st Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails
86 The 1st Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails {Server1 s HW, Server2 s HW}
87 The 2nd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails Fault Sets {Server1 s HW, Server2 s HW}
88 The 2nd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails 1 or 0 1 or 0 1 or 0 Fault Sets {Server1 s HW, Server2 s HW}
89 The 2nd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails {Server1 s HW, Server2 s HW}
90 The 2nd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails {Server1 s HW, Server2 s HW}
91 The 3rd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Server2 s HW fails Fault Sets {Server1 s HW, Server2 s HW}
92 The 3rd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails {Server1 s HW, Server2 s HW}
93 The 3rd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails {Server1 s HW, Server2 s HW}
94 The 3rd Sampling Round Redundancy configuration fails Server 1 fails Server 2 fails +" +" Server1 s HW fails Switch1 fails Fault Sets Server2 s HW fails {Server1 s HW, Server2 s HW} {Switch1}
95 After Many (e.g., 10 7 ) Rounds Fault Sets {Server1 s HW, Server2 s HW} {Switch1} {Switch1, Server2 s HW} {Switch1} {Switch1, Server2 s HW}......
96 Size-Based Ranking Fault Sets {Server1 s HW, Server2 s HW} {Switch1} {Switch1, Server2 s HW} {Switch1} {Switch1, Server2 s HW}......
97 Size-Based Ranking Fault Sets {Switch1} {Switch1} {Switch1, Server2 s HW} {Switch1, Server2 s HW} {Server1 s HW, Server2 s HW}......
98 Independence Evaluation Multiple equations for option: - summation of sizes - weighted average of sizes Fault Sets {Switch1} {Switch1} {Switch1, Server2 s HW} {Switch1, Server2 s HW} {Server1 s HW, Server2 s HW}......
99 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
100 RoadMap Step2 Step1 Step4 Dependency Data Source1 INDaaS Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
101 RoadMap Step2 Step1 Step4 Data Source1 (Cloud1) INDaaS Step3 Step5 Step4 Step2 Data Source2 (Cloud2) #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
102 Service Provider INDaaS Agent Cloud A Cloud B Cloud C
103 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
104 Service Provider Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
105 Trusted Third-Party Service Provider Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
106 Trusted Third-Party Service Provider Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent Cloud providers are reluctant to share this information! Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
107 Secure Multiparty Computation (SMPC) Service Provider Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent SMPC Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
108 Secure Multiparty Computation (SMPC) Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent SMPC is hard to scale! SMPC [Xiao et al. CCSW 13] Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
109 Service Provider Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
110 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
111 Service Provider INDaaS Agent Evaluating independence by the dataset similarity between clouds Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
112 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
113 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
114 App Provider INDaaS Auditor Agent ISP A Power A Power B ISP B Power A Power B Using Jaccard similarity to evaluate the ISP B Power C independence of each redundancy configuration. Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
115 App Provider INDaaS Agent S1 S Sn J(S1, S2,..., Sn) = ISP A Power A Power B ISP B Power A Power B S1 S Sn ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
116 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
117 Service Provider INDaaS Agent ISP A Power A Power B =2 =4 ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
118 Service Provider INDaaS Agent ISP A Power A Power B =2 =4 ISP B Power A Power B ISP B Power C J = 2/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
119 Deployment Sim Cloud A&B 0.5 Service Provider INDaaS Agent ISP A Power A Power B =2 =4 ISP B Power A Power B ISP B Power C J = 2/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
120 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B =1 =4 ISP B Power C J = 1/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
121 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Cloud A&C 0 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
122 Service Provider 0 means fully independent INDaaS Agent Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Cloud A&C 0 ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
123 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Cloud A&C 0 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
124 Deployment Sim Cloud A&C 0 Cloud B&C 0.25 Cloud A&B 0.5 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
125 Deployment Sim Cloud A&C 0 Cloud B&C 0.25 Cloud A&B 0.5 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
126 P-SOP [Vaidya et al. JCS05] We apply Private Set Operation Protocol (P-SOP): - Private set intersection cardinality. - Private set union cardinality. S1 S Sn J(S1, S2,..., Sn) = S1 S Sn
127 P-SOP [Vaidya et al. JCS05] Allow k parties to compute both intersection and union cardinalities without learning other information.
128 P-SOP [Vaidya et al. JCS05] Allow k parties to compute both intersection and union cardinalities without learning other information
129 P-SOP [Vaidya et al. JCS05] Allow k parties to compute both intersection and union cardinalities without learning other information P-SOP
130 P-SOP [Vaidya et al. JCS05] Allow k parties to compute both intersection and union cardinalities without learning other information =1, = =1, =7 =1, =7 P-SOP
131 P-SOP [Vaidya et al. JCS05] Allow k parties to compute both intersection and union cardinalities without learning other information. But I do not know which elements are overlapping/union. Protocol P-SOP 3 7 But I do not know which elements are overlapping/union. But I do not know which elements are overlapping/union
132 P-SOP [Vaidya et al. JCS05] 3 7 Kf Kd Ke Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
133 P-SOP [Vaidya et al. JCS05] 3 7 Kf Kd Ke Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
134 P-SOP [Vaidya et al. JCS05] 3 7 Kf Kd Ke Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
135 P-SOP [Vaidya et al. JCS05] Ee(Ed(Ef(3))) 3 Ee(Ed(Ef(7))) 7 Kf Ef(Ee(Ed(3))) 11 Ef(Ee(Ed(10))) 3 Ef(Ee(Ed(11))) 10 Kd Ke Ed(Ef(Ee(3))) 1 Ed(Ef(Ee(5))) 5 Ed(Ef(Ee(1))) 20 Ed(Ef(Ee(20))) 3 Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
136 P-SOP [Vaidya et al. JCS05] Ee(Ed(Ef(3))) 3 Ee(Ed(Ef(7))) 7 Kf Ef(Ee(Ed(3))) 11 Ef(Ee(Ed(10))) 3 Ef(Ee(Ed(11))) 10 Kd Ke Ed(Ef(Ee(3))) 1 Ed(Ef(Ee(5))) 5 Ed(Ef(Ee(1))) 20 Ed(Ef(Ee(20))) 3 Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
137 P-SOP [Vaidya et al. JCS05] Ee(Ed(Ef(3))) 3 Ee(Ed(Ef(7))) 7 Kf Ef(Ee(Ed(3))) 11 Ef(Ee(Ed(10))) 3 Ef(Ee(Ed(11))) 10 Kd Ke Ed(Ef(Ee(3))) 1 Ed(Ef(Ee(5))) 5 Ed(Ef(Ee(1))) 20 Ed(Ef(Ee(20))) 3 Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
138 P-SOP [Vaidya et al. JCS05] Ee(Ed(Ef(3))) 3 Ee(Ed(Ef(7))) 7 Kf Ef(Ee(Ed(3))) 11 Ef(Ee(Ed(10))) 3 Ef(Ee(Ed(11))) 10 Kd Ef(Ee(Ed(3))) Ke Ed(Ef(Ee(3))) 1 Ed(Ef(Ee(5))) 5 Ed(Ef(Ee(1))) 20 Ed(Ef(Ee(20))) 3 Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
139 P-SOP [Vaidya et al. JCS05] Ee(Ed(Ef(3))) 3 Kf Ef(Ee(Ed(3))) 11 Kd Ef(Ee(Ed(3))) Ef(Ee(Ed(10))) Ef(Ee(Ed(11))) Ee(Ed(Ef(7))) Ed(Ef(Ee(5))) Ed(Ef(Ee(1))) Ed(Ef(Ee(20))) Ke Ed(Ef(Ee(3))) 1 Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
140 P-SOP [Vaidya et al. JCS05] Kf Kd Ef(Ee(Ed(3))) Ef(Ee(Ed(10))) Ef(Ee(Ed(11))) Ee(Ed(Ef(7))) Ed(Ef(Ee(5))) Ed(Ef(Ee(1))) Ed(Ef(Ee(20))) 7 Ke Each party maintains a commutative encryption key Commutative encryption holds: Ex(Ey(m)) = Ey(Ex(m))
141 Private Independence Evaluation
142 Service Provider Select two clouds for redundancy: A&B? B&C? or A&C? INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
143 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
144 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
145 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
146 Service Provider INDaaS Agent ISP A Power A Power B P-SOP ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
147 Service Provider INDaaS Agent ISP A Power A Power B =2 ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
148 Service Provider INDaaS Agent ISP A Power A Power B =2 =4 ISP B Power A Power B ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
149 Service Provider INDaaS Agent ISP A Power A Power B =2 =4 ISP B Power A Power B ISP B Power C J = 2/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
150 Deployment Sim Cloud A&B 0.5 Service Provider INDaaS Agent ISP A Power A Power B =2 =4 ISP B Power A Power B ISP B Power C J = 2/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
151 Deployment Sim Cloud A&B 0.5 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B P-SOP ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
152 Deployment Sim Cloud A&B 0.5 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B =1 =4 ISP B Power C J = 1/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
153 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Service Provider INDaaS Agent ISP A Power A Power B ISP B Power A Power B =1 =4 ISP B Power C J = 1/4 Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
154 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Service Provider INDaaS Agent ISP A Power A Power B P-SOP ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
155 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
156 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Cloud A&C 0 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
157 Deployment Sim Cloud A&B 0.5 Cloud B&C 0.25 Cloud A&C 0 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
158 Deployment Sim Cloud A&C 0 Cloud B&C 0.25 Cloud A&B 0.5 Service Provider INDaaS Agent ISP A Power A Power B =0, =5, J = 0/5 ISP B Power C Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
159 Deployment Sim Cloud A&C 0 Cloud B&C 0.25 Cloud A&B 0.5 Service Provider INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
160 Service Provider Deployment Sim Cloud A&C 0 Cloud B&C 0.25 Cloud A&B 0.5 INDaaS Agent Cloud A Cloud B Cloud C ISP A Power A Power B ISP B Power C
161 RoadMap Step2 Step1 INDaaS Agent Step4 Dependency Data Source1 Step3 Step5 Step4 Step2 Dependency Data Source2 #1: Dependency collections - Solution: Reusing existing tools #2: Dependency representation - Solution: Fault graphs #3: Efficient auditing - Solution: Failure sampling algorithm #4: Private independence audit - Solution: Private Jaccard similarity
162 Evaluation
163 Evaluation Three realistic case studies. Tradeoff between auditing algorithms Overhead of P-SOP protocol
164 Evaluation Three realistic case studies. Tradeoff between auditing algorithms Overhead of P-SOP protocol
165 Three Case Studies Common network dependency Common hardware dependency Common software dependency Please see our paper for more details
166 Evaluation Three realistic case studies. Tradeoff between auditing algorithms Overhead of P-SOP protocol
167 Tradeoff Evaluation We evaluate efficiency/accuracy tradeoff. We generate topology based on fat tree model. We also bu
168 Tradeoff Evaluation Topology A Topology B Topology C # of Core Routers # of Agg Switches ,152 # of ToR Switches ,152 # of Servers 1,024 3,456 27,648 Total # of devices 1,344 4,176 30,528
169 Tradeoff Evaluation Topology A Topology B Topology C # of Core Routers # of Agg Switches ,152 # of ToR Switches ,152 # of Servers 1,024 3,456 27,648 Total # of devices 1,344 4,176 30,528
170 Topology C: 30,528 Devices Minimal Fault Set Algorithm % critical fault sets detected Failure Sampling Algorithm (10 4 ) Minimal Fault Set Algorithm Failure Sampling Algorithm Computational time (minutes) Failure Sampling Algorithm (10 6 )
171 Topology C: 30,528 Devices Minimal Fault Set Algorithm % critical fault sets detected Failure Sampling Algorithm (10 4 ) Minimal Fault Set Algorithm Failure Sampling Algorithm Computational time (minutes) Failure Sampling Algorithm (10 6 )
172 Evaluation Three realistic case studies. Tradeoff between auditing algorithms Overhead of P-SOP protocol
173 What we evaluate? Kissner and Song (KS) protocol for comparison. Bandwidth overhead of P-SOP and KS. Computational overhead of P-SOP and KS.
174 Bandwidth Overhead Total traffic sent (MB) KS (4) P-SOP (4) KS (3) P-SOP (3) KS (2) P-SOP (2) Number of elements in each provider s dataset
175 Bandwidth Overhead Total traffic sent (MB) KS (4) P-SOP (4) KS (3) P-SOP (3) KS (2) P-SOP (2) Number of elements in each provider s dataset
176 Bandwidth Overhead Total traffic sent (MB) KS (4) P-SOP (4) KS (3) P-SOP (3) KS (2) P-SOP (2) Number of elements in each provider s dataset ~80MB
177 Computational Overhead Computational time (seconds) 1e KS (4) KS (3) KS (2) P-SOP (4) P-SOP (3) P-SOP (2) Number of elements in each provider s dataset ~10 3 sec
178 Conclusions INDaaS is a first step towards reliable clouds: - Dependency collections - Dependency representations - Efficient auditing - Private independence auditing We evaluated INDaas with three realistic case studies and large-scale simulations.
179 Thanks, questions? INDaaS: Heading off correlated failures in clouds Find out more at: - We will be at the poster session tonight.
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