Practical Aspects of IP based Take Over Mechanisms. Christof Fetzer, Neeraj Suri AT&T Labs Research, Florham Park, NJ TU Darmstadt, Germany



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Transcription:

Practical Aspects of IP based Take Over Mechanisms Christof Fetzer, Neeraj Suri AT&T Labs Research, Florham Park, NJ TU Darmstadt, Germany

Motivation Problem: What is a good way to increase the availability of wide area services by handling server failures? Holy Grail: Transparent replication? (Transparent: client service sustained & replicated without any (a) client action or (b) modification of C/S code)

Outline Classical Replication: Problems? + Possible Solutions Alternatives: Simple Fail Over Stateless Basis Co ordination Load Balancing/Shedding

Target Application Domain client client client Service

Transparent Replication client client client request

Transparent Replication client client client request Service

Transparent Replication client client client request Service

Transparent Replication client client client atomic broadcast request 1 2 1 2 Service

Protocol Issues client request via TCP or UDP

Potential Solution: Atomic Broadcast Tunnel client Translate TCP to atomic broadcast AB? TCP

Administrative Issue client client client administrative domains

Network Performance client low throughput / high latency high throughput / low latency

Side Broadcast client client client Request via TCP Service

Total Ordering Needed? 1 1 2 2

Total Ordering Not Sufficient 1 1 2 2 T1 T2 T1 T2 Thread

Leader/Follower Protocol T1 T2 L/F Protocol T1 T2 Thread

Transparent 1 n TCP client M2 M1 M2 M1 Replication of input queues sufficient

Target Application Domain client client client SAMBA SAMBA Service

Issues Coping with non determinism is difficult. Leader/Follower protocol is not easy to implement not easy to keep up to date not easy to harden Software bugs: all replicas fail at same point Clients have failure detectors how do they fit in? Different apps detect failures at different times? Support for service/server specific clients?

Is transparent replication all that great even if we can implement it? As clients can detect failures and re connect is simpler IP take over more practical?

Approach: Simple Fail Over Internet unreliable: loss of connection to server must be expected many clients try to reconnect For many services, a simple fail over might be sufficient: Single host system: typically, a crashed server is automatically restarted, Extension of multi host system: If host crashes, server is restarted on a different host

Stateless s client request 1 3 reply 2 inter request state dependable storage system

Recovery client request inter request state dependable storage system

Simple IP Take Over client request via TCP or UDP IP Addr

Simple IP Take Over client IP Addr IP Addr

Implementation IP Addr Only leader has the right to use the service IP address

Requirements At most one leader at a time Infinitely often there is a leader Correct server with the highest priority becomes leader (unless a failure occurs) Only a failure can lead to a leader change [leader stability]

Load Balancing & Fail Over For small work loads, a single server solution is typically sufficient For large work loads, load balancing combined with fail over might be needed.

Load Balancing client client client Load balancer

Issues Dynamic mapping of clients to servers: Load balancer needs to keep state (? fail over more difficult) $ Can be expensive (may need to pay for dynamically changing load balancer mapping) Static mapping of clients to server: No dynamic adjustment of load possible

IP Take Over Solution client client client Load balancer IP1 IPn Static mapping of clients to virtual IP addresses

Dynamic Mapping Each virtual IP address mapped on at most one server Load shedding by not assigning all virtual IP addresses IP2 IPn IP1 IP5 IP3

Membership Based Solution is assigned virtual IP addresses based on current membership Possible Extension: Add load info to membership view Load info facilitates dynamic load balancing

Example s T1 T2 Time S1 IP1 IP1, IP3 IP1, IP3 S2 IP2 IP2 Load shedding S3 IP3 Assigned IP address(es) V={S1,S2, S3} V={S1,S2} Membership Views V={S1}

Requirements Synchronized clocks Agreement on membership view and time when new view becomes valid Each host assumes IP addresses at change of membership: f(view, time, IP)? host

Conclusion IP based replication mechanisms have advantages for classical client transparency Transparent replication only makes sense for certain services Stateless server designs are simple and provide good fail over properties Future work: Add load information hooks to membership protocol