1. Khorramshahr: A Scalable Peer to Peer Architecture for Port Warehouse Management System

2. Outline 01
Introduction 04
The Architecture of Khorramshahr 02
Problem Statement 05
Performance Evaluation 03
Preliminaries of The Used Filters 06
Conclustion

3. Introduction Management of products in huge warehouse
Stock checking is a time consuming task and requires considerable effort
Internet of Things in Smart Industry
Management of products in huge warehouse
Product moves from one warehouse to another
Port the key gateway to industrial products

4. Innovations Khorramshahr uses a peer to peer (P2P) architectural style
which makes it scalable in the number of transactions,
number of warehouses and the geographical distribution.
Memory efficient data structures such as Bloom filter and
Quotient filter are utilized to reduce the response time and
memory usage. Chord based DHT is implemented with
both of the filters and the performances are analyzed
The double chord approach on both distributed hash tables
(product types and product information) is used, to facilitate
users from inside or outside of the port to access the
required information from different warehouses.
To increase the efficiency of the system in looking up product types in object name server (ONS) which is usually in variant, a client server architectural style with replicated
data repository is used. Therefore, Khorramshahr is a hybrid
architecture, which uses both P2P and client server
styles in different sections.
A distributed discovery service is designed to support access
to the product catalogs, stock and property checking.

5. EPC Global Architecture
Physical Components
Radio Frequency Identification (RFID)
RFID Reader
Soft ware Components
Middleware
EPC Information Service (EPCIS)
Object Name Service (ONS)
Discovery Service (DS)

6. Problem Statement W = {w1;w2; …; wm} w= warehouse (1)
T= {t1; t2; …; tn} T= good types (2)
G = {g1; g2; …; gx} G= goods (3)
Wti = {tij |t j ∈ T} (4)
C={c1, c2,…ck,…., cp} C= companies (5)
Cwk = {wi |wi ∈ W} (6)
∩k=1 p Cwk = ∅ (7)
f (gj) = wi
G W (8)

7. Preliminaries of the used filters
Bloom filter A: a vector of bits initially all set to 0s
Preliminaries of the used filters 14 13 12 11 10 9 8 7 6 5 4 3 2 1
Dynamic Bloom Filter
Programming phase: insert each element xi in S into the A, A[Hj(xi)]=1 1 x1 x2 x3
Quotient Filter
Querying phase: if all A[Hj(y)]=1 return Yes
with false positive probability, otherwise return No 1 y1 y2
y1 is definitely not a
member of S
y2 is a member of S
(false positive)

8. The Architecture of Khorramshahr

9. The Architecture of Khorramshahr
Physical Layer
Product Serial No.
(16bit)
Product Type
Warehouse Prefix
Interface Layer
The assigned ID format for each product in the port
EPC ID
(up to 111 bit)
Assigned ID
(48 bit)
Application Layer
The format of product ID in Khorramshahr architecture

10. The deployment view of the Khorramshahr
architecture

11. The Architecture of Khorramshahr
Behavioral Model
Handling Incoming Shipments
Tracking a Stocked Product
Handling Outgoing Shipments
Stock List

12. Performance Evaluation
Value
Parameter
18000(s)
Simulation Time (Global)
No churn
Num Replica churn Type (Global)
10 Mbps
Ethernet Channel Data Rate (Global)
10(ms)
Ethernet Channel Delay (Global)
[ ]
Num Get Request
60s
Test Interval
300
Test TTL
10(s)
Failure Latency
[25-250]
Number of Terminal
OverSim
( release )
Simulation Tools
OMNET++
Version 4.1

13. Performance Comparison & Scalability

14. Performance comparison & scalability

15. Memory Efficiency

16. False Positive Rate

17. Conclusion New architecture warehouse management
Architecture uses a hybrid of P2P and client server paradigms
The architecture is scalable in terms of the number of requests
and the number of warehouses
To boost the lookup procedure two different filters( Bloom and
Quotient filters)